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Google Keyword Rankings for : reinforcement learning reservoir
1
Reinforcement Learning with Convolutional Reservoir ... - arXiv
https://arxiv.org/abs/1912.04161
In this study, we propose a novel practical approach called reinforcement learning with convolutional reservoir computing (RCRC) model.
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https://arxiv.org/abs/1912.04161
In this study, we propose a novel practical approach called reinforcement learning with convolutional reservoir computing (RCRC) model.
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2
Optimal control with reinforcement learning using reservoir ...
https://ieeexplore.ieee.org/iel5/6221055/6229113/06229529.pdf
Abstract—Optimal control problems could be solved with reinforcement learning. However it is challenging to use it with continuous state and action spaces, ...
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https://ieeexplore.ieee.org/iel5/6221055/6229113/06229529.pdf
Abstract—Optimal control problems could be solved with reinforcement learning. However it is challenging to use it with continuous state and action spaces, ...
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3
Reinforcement learning with convolutional reservoir computing
https://link.springer.com/article/10.1007/s10489-020-01679-3
In this study, we propose a novel practical approach called reinforcement learning with a convolutional reservoir computing (RCRC) model.
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https://link.springer.com/article/10.1007/s10489-020-01679-3
In this study, we propose a novel practical approach called reinforcement learning with a convolutional reservoir computing (RCRC) model.
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4
Adaptive model selection in photonic reservoir ... - Nature
https://www.nature.com/articles/s41598-020-66441-8
A more efficient implementation than deep neural networks is required for reinforcement learning. Reservoir computing has attracted significant ...
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https://www.nature.com/articles/s41598-020-66441-8
A more efficient implementation than deep neural networks is required for reinforcement learning. Reservoir computing has attracted significant ...
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5
Reinforcement Learning with Convolutional ... - AAAI-RLG
http://aaai-rlg.mlanctot.info/2020/papers/AAAI20-RLG_paper_2.pdf
In this study, we pro- pose a novel practical approach called reinforcement learning with convolutional reservoir computing (RCRC) model. The. RCRC model uses a ...
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http://aaai-rlg.mlanctot.info/2020/papers/AAAI20-RLG_paper_2.pdf
In this study, we pro- pose a novel practical approach called reinforcement learning with convolutional reservoir computing (RCRC) model. The. RCRC model uses a ...
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6
Deep Reinforcement Learning: Reservoir ... - OnePetro
https://onepetro.org/IPTCONF/proceedings/20IPTC/2-20IPTC/D021S052R002/154747
Deep Reinforcement Learning: Reservoir Optimization from Pixels ... In this paper, Deep Reinforcement Learning (RL) by pixel data is used to ...
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https://onepetro.org/IPTCONF/proceedings/20IPTC/2-20IPTC/D021S052R002/154747
Deep Reinforcement Learning: Reservoir Optimization from Pixels ... In this paper, Deep Reinforcement Learning (RL) by pixel data is used to ...
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7
Sustainable Reservoir Operation and Control Using a Deep ...
https://meetingorganizer.copernicus.org/EGU22/EGU22-13011.html?pdf
Sustainable Reservoir Operation and Control Using a Deep. Reinforcement Learning Policy Gradient Method. Sadegh Sadeghi Tabas1 and Vidya Samadi2.
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https://meetingorganizer.copernicus.org/EGU22/EGU22-13011.html?pdf
Sustainable Reservoir Operation and Control Using a Deep. Reinforcement Learning Policy Gradient Method. Sadegh Sadeghi Tabas1 and Vidya Samadi2.
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8
Evolutionary-assisted reinforcement learning for reservoir real ...
https://www.sciencedirect.com/science/article/pii/S1995822622001959
In addition, the application of deep learning on well-test interpretation for identifying pressure behavior and characterizing reservoirs was also performed ( ...
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https://www.sciencedirect.com/science/article/pii/S1995822622001959
In addition, the application of deep learning on well-test interpretation for identifying pressure behavior and characterizing reservoirs was also performed ( ...
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9
Reinforcement learning with convolutional reservoir computing
https://dl.acm.org/doi/abs/10.1007/s10489-020-01679-3
In this study, we propose a novel practical approach called reinforcement learning with a convolutional reservoir computing (RCRC) model. The RCRC model uses a ...
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https://dl.acm.org/doi/abs/10.1007/s10489-020-01679-3
In this study, we propose a novel practical approach called reinforcement learning with a convolutional reservoir computing (RCRC) model. The RCRC model uses a ...
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10
Tree‐based reinforcement learning for optimal water reservoir ...
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2009WR008898
Although being one of the most popular and extensively studied approaches to design water reservoir operations, Stochastic Dynamic ...
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https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2009WR008898
Although being one of the most popular and extensively studied approaches to design water reservoir operations, Stochastic Dynamic ...
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11
Efficient reinforcement learning of a reservoir network ... - NCBI
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6712583/
Keywords: working memory, reservoir network, reinforcement learning ... Reservoir networks can model the dynamical and heterogeneous neural activity that ...
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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6712583/
Keywords: working memory, reservoir network, reinforcement learning ... Reservoir networks can model the dynamical and heterogeneous neural activity that ...
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12
Deep Reinforcement Learning for Petroleum Reservoir ...
https://www.linkedin.com/pulse/deep-reinforcement-learning-petroleum-reservoir-ruslan-miftakhov
This article extends the category of artificial intelligence algorithms by applying Deep Reinforcement Learning (DRL) for reservoir production ...
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https://www.linkedin.com/pulse/deep-reinforcement-learning-petroleum-reservoir-ruslan-miftakhov
This article extends the category of artificial intelligence algorithms by applying Deep Reinforcement Learning (DRL) for reservoir production ...
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13
Reinforcement Learning Policy Gradient Methods ... - TigerPrints
https://tigerprints.clemson.edu/cgi/viewcontent.cgi?article=4649&context=all_theses
Reinforcement Learning Policy Gradient Methods for Reservoir. Operation Management and Control. Sadegh Sadeghi Tabas sadeghs@clemson.edu.
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https://tigerprints.clemson.edu/cgi/viewcontent.cgi?article=4649&context=all_theses
Reinforcement Learning Policy Gradient Methods for Reservoir. Operation Management and Control. Sadegh Sadeghi Tabas sadeghs@clemson.edu.
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14
Transferring Evolved Reservoir Features in Reinforcement ...
https://ewrl.files.wordpress.com/2011/08/ewrl2011_submission_25.pdf
Abstract. The major goal of transfer learning is to transfer knowledge acquired on a source task in order to facilitate learning on another, dif-.
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https://ewrl.files.wordpress.com/2011/08/ewrl2011_submission_25.pdf
Abstract. The major goal of transfer learning is to transfer knowledge acquired on a source task in order to facilitate learning on another, dif-.
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15
Machine learning for the subsurface characterization at core ...
https://shareok.org/handle/11244/324149?show=full
Accurate characterization of subsurface hydrocarbon reservoirs is essential for economical oil and gas reservoir development. The characterization of reservoir ...
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https://shareok.org/handle/11244/324149?show=full
Accurate characterization of subsurface hydrocarbon reservoirs is essential for economical oil and gas reservoir development. The characterization of reservoir ...
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16
Machine learning solutions for reservoir characterization ...
https://repositories.lib.utexas.edu/handle/2152/74252
In this work, three major areas in petroleum engineering are addressed and resolved using machine learning: well placement evaluation and optimization, time- ...
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https://repositories.lib.utexas.edu/handle/2152/74252
In this work, three major areas in petroleum engineering are addressed and resolved using machine learning: well placement evaluation and optimization, time- ...
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17
Reservoir Operation Optimization by Reinforcement Learning
https://www.researchgate.net/publication/287851678_Reservoir_Operation_Optimization_by_Reinforcement_Learning
Request PDF | Deep Reinforcement Learning: Reservoir Optimization from Pixels | The application of Artificial Intelligence (AI) methods in the petroleum ...
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https://www.researchgate.net/publication/287851678_Reservoir_Operation_Optimization_by_Reinforcement_Learning
Request PDF | Deep Reinforcement Learning: Reservoir Optimization from Pixels | The application of Artificial Intelligence (AI) methods in the petroleum ...
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18
Reservoir Computing in an Evolutionary Neuromorphic ...
https://trace.tennessee.edu/cgi/viewcontent.cgi?article=7551&context=utk_graddiss
3.2.5 Summary of Neural Networks and Machine Learning Algorithms 31 ... 4 Reservoir Computing and Genetic Algorithms in the TENNLab Framework.
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https://trace.tennessee.edu/cgi/viewcontent.cgi?article=7551&context=utk_graddiss
3.2.5 Summary of Neural Networks and Machine Learning Algorithms 31 ... 4 Reservoir Computing and Genetic Algorithms in the TENNLab Framework.
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19
Reservoir Operation Optimization by Reinforcement Learning
https://www.chijournal.org/Journals/PDF/R227-08
Reservoir Operation Optimization by Reinforcement Learning. M. Mahootchi, H. R.Tizhoosh, and K. Ponnambalam. Planning of reservoir management and optimal ...
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https://www.chijournal.org/Journals/PDF/R227-08
Reservoir Operation Optimization by Reinforcement Learning. M. Mahootchi, H. R.Tizhoosh, and K. Ponnambalam. Planning of reservoir management and optimal ...
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20
Reinforcement learning based automated history matching for ...
https://www.osti.gov/servlets/purl/1853666
The reservoir properties are adjusted using an optimization method (also referred as model calibration) with an objective to predict rates and pressures that.
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https://www.osti.gov/servlets/purl/1853666
The reservoir properties are adjusted using an optimization method (also referred as model calibration) with an objective to predict rates and pressures that.
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21
Efficient Reservoir Management through Deep ... - Teamcore
https://teamcore.seas.harvard.edu/files/teamcore/files/google_dam_arxiv.pdf
Therefore, we leverage reinforcement learning (RL) methods to compute efficient dam operation guidelines in this work. Specifically, we build offline simulators.
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https://teamcore.seas.harvard.edu/files/teamcore/files/google_dam_arxiv.pdf
Therefore, we leverage reinforcement learning (RL) methods to compute efficient dam operation guidelines in this work. Specifically, we build offline simulators.
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22
Application of Machine Learning in the Unconventional Tight ...
https://www.spe.org/en/training/courses/aml-application-machine-learning-unconventional-tight-shale-reservoir-development/
Nowadays, large amount of data related to reservoir properties, drilling, completion, and production is routinely collected in the upstream oil and gas ...
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https://www.spe.org/en/training/courses/aml-application-machine-learning-unconventional-tight-shale-reservoir-development/
Nowadays, large amount of data related to reservoir properties, drilling, completion, and production is routinely collected in the upstream oil and gas ...
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23
Machine Learning's 'Amazing' Ability to Predict Chaos
https://www.quantamagazine.org/machine-learnings-amazing-ability-to-predict-chaos-20180418/
They employed a machine-learning algorithm called reservoir computing to “learn” the dynamics of an archetypal chaotic system called the ...
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https://www.quantamagazine.org/machine-learnings-amazing-ability-to-predict-chaos-20180418/
They employed a machine-learning algorithm called reservoir computing to “learn” the dynamics of an archetypal chaotic system called the ...
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24
Reservoir computing - Wikipedia
https://en.wikipedia.org/wiki/Reservoir_computing
Reservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into higher dimensional ...
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https://en.wikipedia.org/wiki/Reservoir_computing
Reservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into higher dimensional ...
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25
Deep Reinforcement Learning for Optimal ... - ASCE Library
https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29WR.1943-5452.0001409
Optimal operation of hydropower reservoir systems is a classical optimization problem of high dimensionality and stochastic nature.
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https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29WR.1943-5452.0001409
Optimal operation of hydropower reservoir systems is a classical optimization problem of high dimensionality and stochastic nature.
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26
Machine learning procedures for automatic well planning in ...
https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/2977363
Simulation of reservoir models is a tool to optimize the development of an oil and gas reservoir. Part of the development is placement of wells in the ...
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https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/2977363
Simulation of reservoir models is a tool to optimize the development of an oil and gas reservoir. Part of the development is placement of wells in the ...
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27
Deep learning reservoir porosity prediction based on ...
https://library.seg.org/doi/abs/10.1190/geo2019-0261.1
We have developed a machine-learning method based on the traditional long short-term memory (LSTM) model, called multilayer LSTM (MLSTM), to perform the ...
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https://library.seg.org/doi/abs/10.1190/geo2019-0261.1
We have developed a machine-learning method based on the traditional long short-term memory (LSTM) model, called multilayer LSTM (MLSTM), to perform the ...
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28
Quantum reservoir computing for machine learning - YouTube
https://www.youtube.com/watch?v=67Gj5NWQoEM
Gemini Center on Quantum Computing
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https://www.youtube.com/watch?v=67Gj5NWQoEM
Gemini Center on Quantum Computing
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29
Aggregation–Decomposition-Based Multi-Agent ... - MDPI
https://mdpi-res.com/d_attachment/water/water-12-02688/article_deploy/water-12-02688-v4.pdf?version=1603334116
Reinforcement Learning for Multi-Reservoir ... Different optimization models have been used in water reservoir problems through ISO, ...
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https://mdpi-res.com/d_attachment/water/water-12-02688/article_deploy/water-12-02688-v4.pdf?version=1603334116
Reinforcement Learning for Multi-Reservoir ... Different optimization models have been used in water reservoir problems through ISO, ...
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30
Skoltech-CHR/DeepField: Machine learning ... - GitHub
https://github.com/Skoltech-CHR/DeepField
Machine learning framework for reservoir simulation. img. Features. reservoir representation with Grid, Rock, States, Wells, Aquifer and PVT-tables components ...
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https://github.com/Skoltech-CHR/DeepField
Machine learning framework for reservoir simulation. img. Features. reservoir representation with Grid, Rock, States, Wells, Aquifer and PVT-tables components ...
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31
Can Machine Learning Be Used in Long-Term Reservoir ...
https://medium.com/mlearning-ai/can-machine-learning-be-used-in-long-term-reservoir-level-prediction-e088d27e370b
Can Machine Learning Be Used in Long-Term Reservoir Level Prediction? My capstone project on time series prediction at major California reservoirs demonstrates ...
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https://medium.com/mlearning-ai/can-machine-learning-be-used-in-long-term-reservoir-level-prediction-e088d27e370b
Can Machine Learning Be Used in Long-Term Reservoir Level Prediction? My capstone project on time series prediction at major California reservoirs demonstrates ...
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32
Reinforcement learning using reservoir computing for soft ...
https://www.ideals.illinois.edu/handle/2142/114113
Title: Reinforcement learning using reservoir computing for soft robotic control: A bio-inspired system. Author(s):, Shivam, Keshav.
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https://www.ideals.illinois.edu/handle/2142/114113
Title: Reinforcement learning using reservoir computing for soft robotic control: A bio-inspired system. Author(s):, Shivam, Keshav.
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33
Modeling and simulating of reservoir operation using the ...
https://escholarship.org/uc/item/48x0t0b1
The realization of those functions requires efficient reservoir operation, and the ... neural network, support vector regression, deep learning algorithm.
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https://escholarship.org/uc/item/48x0t0b1
The realization of those functions requires efficient reservoir operation, and the ... neural network, support vector regression, deep learning algorithm.
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34
Efficient Reservoir Management through Deep Reinforcement ...
https://www.semanticscholar.org/paper/Efficient-Reservoir-Management-through-Deep-Wang-Nair/06f8acb819ef453390590933c62ebe6d7ef443ce
This paper proposes soft actor-critic, an off-policy actor-Critic deep RL algorithm based on the maximum entropy reinforcement learning ...
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https://www.semanticscholar.org/paper/Efficient-Reservoir-Management-through-Deep-Wang-Nair/06f8acb819ef453390590933c62ebe6d7ef443ce
This paper proposes soft actor-critic, an off-policy actor-Critic deep RL algorithm based on the maximum entropy reinforcement learning ...
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35
Machine Learning Electronics - Nonlinear Dynamics Lab
https://complex.umd.edu/research/machinelearning/machinelearning.php
A reservoir computer (RC; see diagram below) is a type of recurrent neural network, which consists of large arrays of communicating artificial neurons, each one ...
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https://complex.umd.edu/research/machinelearning/machinelearning.php
A reservoir computer (RC; see diagram below) is a type of recurrent neural network, which consists of large arrays of communicating artificial neurons, each one ...
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36
Deep Reinforcement Learning for Constrained Field ...
https://www.frontiersin.org/articles/10.3389/fams.2021.689934/full
This artificial intelligence agent, comprising of a convolutional neural network, provides a mapping from a given state of the reservoir model, ...
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https://www.frontiersin.org/articles/10.3389/fams.2021.689934/full
This artificial intelligence agent, comprising of a convolutional neural network, provides a mapping from a given state of the reservoir model, ...
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37
Applied Machine Learning for Reservoir Characterization ...
https://www.nexttraining.net/course/applied-machine-learning-for-reservoir-characterization-petrophysics-and-surveillance---physics-inspired-principles-applications-and-workflows/3226
Overview closed-loop reservoir surveillance and management. Outline the needs for employing machine learning and AI solutions that are inspired by physics for ...
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https://www.nexttraining.net/course/applied-machine-learning-for-reservoir-characterization-petrophysics-and-surveillance---physics-inspired-principles-applications-and-workflows/3226
Overview closed-loop reservoir surveillance and management. Outline the needs for employing machine learning and AI solutions that are inspired by physics for ...
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38
Dynamic reservoir for developmental reinforcement learning
https://members.loria.fr/ADutech/Papier/dutech11_reservoirDevRL.pdf
Dynamic reservoir for developmental reinforcement learning. Alain Dutech. LORIA - INRIA Campus Scientifique - BP 239. 54506 Vandoeuvre les Nancy, FRANCE.
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https://members.loria.fr/ADutech/Papier/dutech11_reservoirDevRL.pdf
Dynamic reservoir for developmental reinforcement learning. Alain Dutech. LORIA - INRIA Campus Scientifique - BP 239. 54506 Vandoeuvre les Nancy, FRANCE.
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39
Aggregation–Decomposition-Based Multi-Agent ... - MDPI
https://www.mdpi.com/2073-4441/12/10/2688
Reinforcement learning (RL), a simulation-based stochastic ... In this model, each reservoir is individually managed by a specific operator ...
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https://www.mdpi.com/2073-4441/12/10/2688
Reinforcement learning (RL), a simulation-based stochastic ... In this model, each reservoir is individually managed by a specific operator ...
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40
Efficient Reservoir Management through Deep Reinforcement ...
https://crossminds.ai/video/efficient-reservoir-management-through-deep-reinforcement-learning-606fda67f43a7f2f827bf303/
Efficient Reservoir Management through Deep Reinforcement Learning ... SREcon15 - From Zero to Hero: Recommended Practices for Training your Ever-Evolving ...
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https://crossminds.ai/video/efficient-reservoir-management-through-deep-reinforcement-learning-606fda67f43a7f2f827bf303/
Efficient Reservoir Management through Deep Reinforcement Learning ... SREcon15 - From Zero to Hero: Recommended Practices for Training your Ever-Evolving ...
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41
Machine Learning for Reservoir Characterization and Time ...
https://uh-ir.tdl.org/handle/10657/7975
During field development, static reservoir models are built by incorporating well logs, core, and seismic data. However, seismic amplitude data often cannot ...
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https://uh-ir.tdl.org/handle/10657/7975
During field development, static reservoir models are built by incorporating well logs, core, and seismic data. However, seismic amplitude data often cannot ...
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42
Reservoir computing, a machine learning tool for robust ...
https://aip.scitation.org/doi/10.1063/10.0009049
Reservoir computers, networks of nodes that are trainable dynamical systems, are a relatively mature machine learning approach.
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https://aip.scitation.org/doi/10.1063/10.0009049
Reservoir computers, networks of nodes that are trainable dynamical systems, are a relatively mature machine learning approach.
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43
Reservoir Simulations: Machine Learning and Modeling
https://www.amazon.com/Reservoir-Simulations-Machine-Learning-Modeling/dp/0128209577
Reservoir Simulation: Machine Learning and Modeling helps the engineer step into the current and most popular advances in reservoir simulation, learning ...
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https://www.amazon.com/Reservoir-Simulations-Machine-Learning-Modeling/dp/0128209577
Reservoir Simulation: Machine Learning and Modeling helps the engineer step into the current and most popular advances in reservoir simulation, learning ...
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44
Multi-reservoir flood control using deep reinforcement learning
https://www.jstage.jst.go.jp/article/jsceiii/3/3/3_46/_article/-char/en
1) Lee, J. and Labadie, J, W.: Stochastic optimization of multireservoir systems via reinforcement learning, Water Resour. Res., Vol. 43, 2007.
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https://www.jstage.jst.go.jp/article/jsceiii/3/3/3_46/_article/-char/en
1) Lee, J. and Labadie, J, W.: Stochastic optimization of multireservoir systems via reinforcement learning, Water Resour. Res., Vol. 43, 2007.
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45
Reservoir Computing | NextBigFuture.com
https://www.nextbigfuture.com/2021/05/reservoir-computing.html
Reservoir computing is an approach to make machine learning algorithms run faster. The word reservoir refers to a dynamical system.
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https://www.nextbigfuture.com/2021/05/reservoir-computing.html
Reservoir computing is an approach to make machine learning algorithms run faster. The word reservoir refers to a dynamical system.
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46
hardmaru on Twitter: "Reinforcement Learning with ...
https://twitter.com/hardmaru/status/1237917815677452288?lang=en
Reinforcement Learning with Convolutional Reservoir Computing They use a fixed random-weight CNN and a reservoir computing model to extract ...
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https://twitter.com/hardmaru/status/1237917815677452288?lang=en
Reinforcement Learning with Convolutional Reservoir Computing They use a fixed random-weight CNN and a reservoir computing model to extract ...
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47
A neural network model for the orbitofrontal cortex and task ...
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005925
Reinforcement learning helps to shape the output of the reservoir, essentially picking out the action that will lead to the event sequences with ...
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https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005925
Reinforcement learning helps to shape the output of the reservoir, essentially picking out the action that will lead to the event sequences with ...
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48
When machine learning meets complex systems: Networks ...
https://www.pik-potsdam.de/members/kurths/publikationen/2020/tang-2020-5-0016505.pdf
Conversely, machine learning procedures, such as. “reservoir computing” and “long short-term memory”, are often dynamical in nature, and the understanding ...
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https://www.pik-potsdam.de/members/kurths/publikationen/2020/tang-2020-5-0016505.pdf
Conversely, machine learning procedures, such as. “reservoir computing” and “long short-term memory”, are often dynamical in nature, and the understanding ...
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49
Optimal carbon storage reservoir management through deep ...
https://ideas.repec.org/a/eee/appene/v278y2020ics0306261920311569.html
Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was ...
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https://ideas.repec.org/a/eee/appene/v278y2020ics0306261920311569.html
Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was ...
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50
ESE Ph.D. Defense | Jeff Rutherford - Deep Reinforcement ...
https://events.stanford.edu/event/ese_phd_defense_jeff_rutherford_-_deep_reinforcement_learning_for_practical_closed-loop_reservoir_management
ESE Ph.D. Defense | Jeff Rutherford - Deep Reinforcement Learning for Practical Closed-Loop Reservoir Management. Sponsored by.
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https://events.stanford.edu/event/ese_phd_defense_jeff_rutherford_-_deep_reinforcement_learning_for_practical_closed-loop_reservoir_management
ESE Ph.D. Defense | Jeff Rutherford - Deep Reinforcement Learning for Practical Closed-Loop Reservoir Management. Sponsored by.
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51
New Approach to Machine Learning Could Make Chaos More ...
https://www.sciencealert.com/new-approach-to-machine-learning-could-make-chaos-more-predictable
New machine learning could better predict chaotic systems like extreme ... Developed through next-gen reservoir computing techniques, ...
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https://www.sciencealert.com/new-approach-to-machine-learning-could-make-chaos-more-predictable
New machine learning could better predict chaotic systems like extreme ... Developed through next-gen reservoir computing techniques, ...
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52
Self-Adaptive Reservoir Computing with Spiking Neurons ...
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1639995
Mahadevuni, A and Li, P "Navigating mobile robots to target in near shortest time using reinforcement learning with spiking neural networks" Proceedings of ...
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https://www.nsf.gov/awardsearch/showAward?AWD_ID=1639995
Mahadevuni, A and Li, P "Navigating mobile robots to target in near shortest time using reinforcement learning with spiking neural networks" Proceedings of ...
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53
Deep Reinforcement Learning for Optimal Hydropower ...
https://ore.exeter.ac.uk/repository/handle/10871/124834
Optimal operation of hydropower reservoir systems is a classical optimization problem of high dimensionality and stochastic nature.
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https://ore.exeter.ac.uk/repository/handle/10871/124834
Optimal operation of hydropower reservoir systems is a classical optimization problem of high dimensionality and stochastic nature.
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54
"Development of Reduced Order Models Using Reservoir ...
https://digitalcommons.lsu.edu/gradschool_theses/5236/
Jr, "Development of Reduced Order Models Using Reservoir Simulation and Physics Informed Machine Learning Techniques" (2020). LSU Master's Theses. 5236. https ...
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https://digitalcommons.lsu.edu/gradschool_theses/5236/
Jr, "Development of Reduced Order Models Using Reservoir Simulation and Physics Informed Machine Learning Techniques" (2020). LSU Master's Theses. 5236. https ...
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55
Photonic Reinforcement Learning Based ... - Research Square
https://www.researchsquare.com/article/rs-988124/latest.pdf
reinforcement learning using optoelectronic delay-based reservoir computing, both experimentally and numerically. In the proposed scheme, ...
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https://www.researchsquare.com/article/rs-988124/latest.pdf
reinforcement learning using optoelectronic delay-based reservoir computing, both experimentally and numerically. In the proposed scheme, ...
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56
A case study in presalt carbonates of Buzios Field, Brazil | The ...
https://pubs.geoscienceworld.org/tle/article/40/12/876/609993/Geostatistics-assisted-by-machine-learning-for
Geostatistics assisted by machine learning for reservoir property modeling: ... reservoir properties for the intermediate reservoir section.
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https://pubs.geoscienceworld.org/tle/article/40/12/876/609993/Geostatistics-assisted-by-machine-learning-for
Geostatistics assisted by machine learning for reservoir property modeling: ... reservoir properties for the intermediate reservoir section.
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57
Permeability Predictions for Tight Sandstone Reservoir Using ...
https://www.hindawi.com/journals/geofluids/2022/2263329/
However, while considerable progress has recently been made in the machine learning based prediction of reservoir permeability, the generalization of this ...
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https://www.hindawi.com/journals/geofluids/2022/2263329/
However, while considerable progress has recently been made in the machine learning based prediction of reservoir permeability, the generalization of this ...
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58
Learning navigation attractors for mobile robots with ...
http://ericantonelo.com/research/learning-navigation-attractors-mobile-robots-reinforcement-learning-and-reservoir-computing
Learning navigation attractors for mobile robots with reinforcement learning and reservoir computing ... Autonomous robot navigation in partially ...
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http://ericantonelo.com/research/learning-navigation-attractors-mobile-robots-reinforcement-learning-and-reservoir-computing
Learning navigation attractors for mobile robots with reinforcement learning and reservoir computing ... Autonomous robot navigation in partially ...
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59
Reservoir prescriptive management combining electric ...
http://www.aimspress.com/article/id/606d8c67ba35de51d3b0ce6a
Reservoir prescriptive management combining electric resistivity tomography and machine learning[J]. AIMS Geosciences, 2021, 7(2): 138-161. doi: ...
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http://www.aimspress.com/article/id/606d8c67ba35de51d3b0ce6a
Reservoir prescriptive management combining electric resistivity tomography and machine learning[J]. AIMS Geosciences, 2021, 7(2): 138-161. doi: ...
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60
Adaptive reservoir computing through evolution and learning
https://issel.ee.auth.gr/wp-content/uploads/2017/01/Adaptive-reservoir-computing-through-evolution-and-learning.pdf
Reservoir computing. Echo state networks. Neuroevolution. Evolutionary computation. Reinforcement learning. a b s t r a c t. The development of real-world, ...
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https://issel.ee.auth.gr/wp-content/uploads/2017/01/Adaptive-reservoir-computing-through-evolution-and-learning.pdf
Reservoir computing. Echo state networks. Neuroevolution. Evolutionary computation. Reinforcement learning. a b s t r a c t. The development of real-world, ...
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61
Adaptive model selection in photonic ... - Papers With Code
https://paperswithcode.com/paper/adaptive-model-selection-in-photonic
We prepare two types of output weights for the source models, and the system adaptively selected the correct model using reinforcement learning, ...
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https://paperswithcode.com/paper/adaptive-model-selection-in-photonic
We prepare two types of output weights for the source models, and the system adaptively selected the correct model using reinforcement learning, ...
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62
Deep Reinforcement Learning for Optimal Hydropower ...
https://dspace.lib.cranfield.ac.uk/bitstream/handle/1826/16718/Deep_reinforcement_learning_optimal_hydropower_reservoir-2021.pdf?sequence=1
Abstract: Optimal operation of hydropower reservoir systems is a classical optimization problem of high dimensionality and stochastic nature.
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https://dspace.lib.cranfield.ac.uk/bitstream/handle/1826/16718/Deep_reinforcement_learning_optimal_hydropower_reservoir-2021.pdf?sequence=1
Abstract: Optimal operation of hydropower reservoir systems is a classical optimization problem of high dimensionality and stochastic nature.
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63
Application of Machine Learning Algorithms in Hydrocarbon ...
https://repository.arizona.edu/handle/10150/628470?show=full
Application of Machine Learning Algorithms in Hydrocarbon Exploration and Reservoir Characterization ; dc.date.accessioned, 2018-08-10T22:17:08Z.
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https://repository.arizona.edu/handle/10150/628470?show=full
Application of Machine Learning Algorithms in Hydrocarbon Exploration and Reservoir Characterization ; dc.date.accessioned, 2018-08-10T22:17:08Z.
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64
Reinforcement learning in a large-scale photonic recurrent ...
https://opg.optica.org/abstract.cfm?uri=optica-5-6-756
Among others, these systems are now capable of solving non-trivial computational problems in optics [2]. At the same time, reservoir computing (RC) emerged as a ...
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https://opg.optica.org/abstract.cfm?uri=optica-5-6-756
Among others, these systems are now capable of solving non-trivial computational problems in optics [2]. At the same time, reservoir computing (RC) emerged as a ...
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65
Physics-informed Machine Learning for Real-time ... - CEUR-WS
https://ceur-ws.org/Vol-2587/article_10.pdf
Current extraction efficiency from unconventional reservoir is very low (~5-10%) for tight oil and ~20% for shale gas (Sandrea, 2007; Muggeridge et al., 2014) ...
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https://ceur-ws.org/Vol-2587/article_10.pdf
Current extraction efficiency from unconventional reservoir is very low (~5-10%) for tight oil and ~20% for shale gas (Sandrea, 2007; Muggeridge et al., 2014) ...
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66
Machine-learning potential of a single pendulum
https://link.aps.org/doi/10.1103/PhysRevE.105.054203
Reservoir computing offers a great computational framework where a physical system can directly be used as computational substrate.
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https://link.aps.org/doi/10.1103/PhysRevE.105.054203
Reservoir computing offers a great computational framework where a physical system can directly be used as computational substrate.
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67
Reservoir optimization and Machine Learning methods
https://www.fime-lab.org/wp-content/uploads/2016/07/StorageAndMachineLearning.pdf
Reservoir optimization and Machine Learning methods. Xavier Warin. ∗. June 24, 2021. Abstract. After showing the efficiency of feedforward networks to ...
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https://www.fime-lab.org/wp-content/uploads/2016/07/StorageAndMachineLearning.pdf
Reservoir optimization and Machine Learning methods. Xavier Warin. ∗. June 24, 2021. Abstract. After showing the efficiency of feedforward networks to ...
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68
Application of Deep Learning in Reservoir Simulation | Earthdoc
https://www.earthdoc.org/content/papers/10.3997/2214-4609.201902252
Then, based on these attributes, flow equations are solved with time-consuming numerical methods. Given the recent progress in machine learning, ...
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https://www.earthdoc.org/content/papers/10.3997/2214-4609.201902252
Then, based on these attributes, flow equations are solved with time-consuming numerical methods. Given the recent progress in machine learning, ...
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69
CX-101537: Machine Learning Approaches to Predicting ...
https://www.energy.gov/nepa/downloads/cx-101537-machine-learning-approaches-predicting-induced-seismicity-and-imaging
CX-101537: Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties. July 22, 2019. AddThis Sharing Buttons.
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https://www.energy.gov/nepa/downloads/cx-101537-machine-learning-approaches-predicting-induced-seismicity-and-imaging
CX-101537: Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties. July 22, 2019. AddThis Sharing Buttons.
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70
Scientists Use Machine Learning To Peer Into the Future
https://scitechdaily.com/scientists-use-machine-learning-to-peer-into-the-future/
The researchers utilize an advanced machine learning method known as next generation reservoir computing. Chaotic physical processes are now ...
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https://scitechdaily.com/scientists-use-machine-learning-to-peer-into-the-future/
The researchers utilize an advanced machine learning method known as next generation reservoir computing. Chaotic physical processes are now ...
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71
Modeling subsurface performance of a geothermal reservoir ...
https://pubs.er.usgs.gov/publication/70231484
In this study, we describe a new approach combining reservoir modeling and machine learning to produce models that enable such a strategy.
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https://pubs.er.usgs.gov/publication/70231484
In this study, we describe a new approach combining reservoir modeling and machine learning to produce models that enable such a strategy.
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72
Machine Learning to Improve Natural Gas Reservoir Simulations
https://cgi.csc.liv.ac.uk/~frans/PostScriptFiles/choubinehEtAlBookChapter_2021.pdf
Reservoir simulation methods applied to gas reservoirs are reviewed and the key influencing variables identified. Machine Learning (ML) methods can be applied ...
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https://cgi.csc.liv.ac.uk/~frans/PostScriptFiles/choubinehEtAlBookChapter_2021.pdf
Reservoir simulation methods applied to gas reservoirs are reviewed and the key influencing variables identified. Machine Learning (ML) methods can be applied ...
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73
Hamiltonian-Reservoir Replica Exchange and Machine ...
https://pubs.acs.org/doi/10.1021/acs.jctc.0c00100
This work combines a machine learning potential energy function with a modular enhanced sampling scheme to obtain statistically converged ...
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https://pubs.acs.org/doi/10.1021/acs.jctc.0c00100
This work combines a machine learning potential energy function with a modular enhanced sampling scheme to obtain statistically converged ...
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74
Efficient reinforcement learning of a reservoir network model ...
https://journals.physiology.org/doi/full/10.1152/jn.00378.2015
Efficient reinforcement learning of a reservoir network model of parametric working memory achieved with a cluster population winner-take-all readout ...
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https://journals.physiology.org/doi/full/10.1152/jn.00378.2015
Efficient reinforcement learning of a reservoir network model of parametric working memory achieved with a cluster population winner-take-all readout ...
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75
Integrating Episodic Memory into a Reinforcement Learning ...
https://openreview.net/forum?id=ByJDAIe0b
External memory for online reinforcement learning based on estimating gradients over a novel reservoir sampling technique.
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https://openreview.net/forum?id=ByJDAIe0b
External memory for online reinforcement learning based on estimating gradients over a novel reservoir sampling technique.
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76
Reservoir Computing & Its Significance In Machine Learning
https://analyticsindiamag.com/reservoir-computing-machine-learning-neural-networks/
Reservoir computing is an approach to make machine learning algorithms run faster. The word reservoir refers to a dynamical system.
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https://analyticsindiamag.com/reservoir-computing-machine-learning-neural-networks/
Reservoir computing is an approach to make machine learning algorithms run faster. The word reservoir refers to a dynamical system.
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77
Development of machine learning predictive models for ...
https://academic.oup.com/jge/article/15/5/2235/5205108
Abstract. History matching (HM) is an important task that is performed once a reliable reservoir model is constructed during numerical reservoir simulation ...
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https://academic.oup.com/jge/article/15/5/2235/5205108
Abstract. History matching (HM) is an important task that is performed once a reliable reservoir model is constructed during numerical reservoir simulation ...
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78
Reinforcement Learning with Convolutional ... - DeepAI
https://deepai.org/publication/reinforcement-learning-with-convolutional-reservoir-computing
12/05/19 - Recently, reinforcement learning models have achieved great success, mastering complex tasks such as Go and other games with ...
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https://deepai.org/publication/reinforcement-learning-with-convolutional-reservoir-computing
12/05/19 - Recently, reinforcement learning models have achieved great success, mastering complex tasks such as Go and other games with ...
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79
machine learning - Question on reservoir sampling
https://datascience.stackexchange.com/questions/8069/question-on-reservoir-sampling
Consider the class to be the variable that you are sampling. Your "reservoir sample" should still be as good as uniformly drawn from your data.
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https://datascience.stackexchange.com/questions/8069/question-on-reservoir-sampling
Consider the class to be the variable that you are sampling. Your "reservoir sample" should still be as good as uniformly drawn from your data.
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80
Efficient reinforcement learning of a reservoir network model ...
https://europepmc.org/article/pmc/pmc6712583
Efficient reinforcement learning of a reservoir network model of parametric working memory achieved with a cluster population ...
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https://europepmc.org/article/pmc/pmc6712583
Efficient reinforcement learning of a reservoir network model of parametric working memory achieved with a cluster population ...
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81
A Beginner's Guide to Deep Reinforcement Learning | Pathmind
https://wiki.pathmind.com/deep-reinforcement-learning
Reinforcement learning refers to goal-oriented algorithms, which learn how to attain a complex objective (goal) or maximize along a particular dimension ...
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https://wiki.pathmind.com/deep-reinforcement-learning
Reinforcement learning refers to goal-oriented algorithms, which learn how to attain a complex objective (goal) or maximize along a particular dimension ...
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82
Jobs | SLB Careers
https://careers.slb.com/job-listing
Mechanical Design Engineer, RPF - RPI (Reservoir Performance Intervention) ... Internship - Leverage Machine Learning to increase tender win-rates !
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https://careers.slb.com/job-listing
Mechanical Design Engineer, RPF - RPI (Reservoir Performance Intervention) ... Internship - Leverage Machine Learning to increase tender win-rates !
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83
Spe Fundamentals Of Drilling Engineering Read Pdf Free
https://home.prospera.or.id/cgi/lowpoly?z=K6G7O6&FileName=Spe_Fundamentals_Of_Drilling_Engineering
Teaches how to apply machine learning algorithms that work best in exploration, drilling, reservoir or production engineering Helps readers ...
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https://home.prospera.or.id/cgi/lowpoly?z=K6G7O6&FileName=Spe_Fundamentals_Of_Drilling_Engineering
Teaches how to apply machine learning algorithms that work best in exploration, drilling, reservoir or production engineering Helps readers ...
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84
Visual Object Recognition Bastian Leibe Pdf
https://intranet.ulc.edu.pe/contentview?racknumber=28047&FileName=visual%20object%20recognition%20bastian%20leibe.pdf
of machine learning that are seldom touched upon in other books. ... and Reservoir Computing, Reinforcement Learning, Reservoir Computing,.
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https://intranet.ulc.edu.pe/contentview?racknumber=28047&FileName=visual%20object%20recognition%20bastian%20leibe.pdf
of machine learning that are seldom touched upon in other books. ... and Reservoir Computing, Reinforcement Learning, Reservoir Computing,.
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85
OATD – Open Access Theses and Dissertations
https://oatd.org/
서, 민지. Ajou University. DNA Nanostructures for Nanopore-based Digital Assays. He, Liqun. University of Ottawa. Machine Learning ...
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https://oatd.org/
서, 민지. Ajou University. DNA Nanostructures for Nanopore-based Digital Assays. He, Liqun. University of Ottawa. Machine Learning ...
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86
Learn how Deep Reinforcement Learning helps businesses ...
https://nealanalytics.com/blog/learn-how-deep-reinforcement-learning-helps-businesses-solve-complex-problems-with-examples/
Reinforcement learning is a goal-oriented AI training algorithm that uses a trial-and-error approach. Learn this using real-life examples.
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https://nealanalytics.com/blog/learn-how-deep-reinforcement-learning-helps-businesses-solve-complex-problems-with-examples/
Reinforcement learning is a goal-oriented AI training algorithm that uses a trial-and-error approach. Learn this using real-life examples.
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87
Subsurface Digital & AI Solutions Expert - Naukrigulf.com
https://www.naukrigulf.com/subsurface-digital-ai-solutions-expert-jobs-in-abu-dhabi-uae-in-mph-global-services-20-to-30plus-years-p-cd-19769-jid-251122000032
... predictive analytics, machine learning and big data, including Autonomous Well Control, Data-driven Reservoir Modelling for Production ...
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https://www.naukrigulf.com/subsurface-digital-ai-solutions-expert-jobs-in-abu-dhabi-uae-in-mph-global-services-20-to-30plus-years-p-cd-19769-jid-251122000032
... predictive analytics, machine learning and big data, including Autonomous Well Control, Data-driven Reservoir Modelling for Production ...
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88
Mapping Lyme disease out west | EurekAlert!
https://www.eurekalert.org/news-releases/971978
They then employed machine learning to correlate tick infection rates ... small mammals that can serve as a reservoir for B. burgdorferi.
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https://www.eurekalert.org/news-releases/971978
They then employed machine learning to correlate tick infection rates ... small mammals that can serve as a reservoir for B. burgdorferi.
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89
Mapping Lyme disease across western North America
https://phys.org/news/2022-11-lyme-disease-western-north-america.html
They then employed machine learning to correlate tick infection rates ... small mammals that can serve as a reservoir for B. burgdorferi.
→ Check Latest Keyword Rankings ←
https://phys.org/news/2022-11-lyme-disease-western-north-america.html
They then employed machine learning to correlate tick infection rates ... small mammals that can serve as a reservoir for B. burgdorferi.
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90
Computer Modelling Group (TSE:CMG) Hits New 52-Week ...
https://reporter.am/2022/11/27/computer-modelling-group-tsecmg-hits-new-52-week-high-at-5-67.html
... for reservoir by combining statistical analysis, machine learning, ... and CoFlow, a reservoir and production system modelling software ...
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https://reporter.am/2022/11/27/computer-modelling-group-tsecmg-hits-new-52-week-high-at-5-67.html
... for reservoir by combining statistical analysis, machine learning, ... and CoFlow, a reservoir and production system modelling software ...
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91
AI in Oil & Gas Market Key Players, End User, Demand and ...
https://www.digitaljournal.com/pr/ai-in-oil-gas-market-key-players-end-user-demand-and-analysis-growth-trends-by-2032-leading-players-ibm-accenture-google-microsoft-corporation
... dwelling, exploration, tank and reservoir monitoring, ... of tools such as machine learning, artificial neutral networks, fuzzy logic, ...
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https://www.digitaljournal.com/pr/ai-in-oil-gas-market-key-players-end-user-demand-and-analysis-growth-trends-by-2032-leading-players-ibm-accenture-google-microsoft-corporation
... dwelling, exploration, tank and reservoir monitoring, ... of tools such as machine learning, artificial neutral networks, fuzzy logic, ...
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92
Aramco: Where Energy is Opportunity
https://www.aramco.com/
... Training, employee development and capacity building ... integration of four technologies: multilateral, maximum reservoir contact (MRC) wells; ...
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https://www.aramco.com/
... Training, employee development and capacity building ... integration of four technologies: multilateral, maximum reservoir contact (MRC) wells; ...
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93
Machine Learning Applications in Subsurface Energy Resource ...
https://books.google.com/books?id=GGudEAAAQBAJ&pg=PT20&lpg=PT20&dq=reinforcement+learning+reservoir&source=bl&ots=ZtFGOUo-Qr&sig=ACfU3U1agXED3VM1Yn7pDCuAX086HiJ-dw&hl=en&sa=X&ved=2ahUKEwjY_ODH2dH7AhXCjYkEHU8GA9cQ6AF6BQi5AhAD
Chapter 10, “Machine Learning Assisted Forecasting of Reservoir Performance (Artun),” focuses on ML-based performance forecasting models that are purely ...
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https://books.google.com/books?id=GGudEAAAQBAJ&pg=PT20&lpg=PT20&dq=reinforcement+learning+reservoir&source=bl&ots=ZtFGOUo-Qr&sig=ACfU3U1agXED3VM1Yn7pDCuAX086HiJ-dw&hl=en&sa=X&ved=2ahUKEwjY_ODH2dH7AhXCjYkEHU8GA9cQ6AF6BQi5AhAD
Chapter 10, “Machine Learning Assisted Forecasting of Reservoir Performance (Artun),” focuses on ML-based performance forecasting models that are purely ...
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