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Echo state network-based Q-learning method for optimal battery control of offices combined with renewable energy 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2017, 卷号: 11, 期号: 7, 页码: 915-922
作者:  Shi, Guang;  Liu, Derong;  Wei, Qinglai
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Recurrent Neural Nets  Neurocontrollers  Learning (Artificial Intelligence)  Office Environment  Optimal Control  Solar Power  Energy Consumption  Time Series  Secondary Cells  Energy Management Systems  Function Approximation  Echo State Network-based Q-learning Method  Optimal Battery Control  Renewable Energy  Optimal Energy Management  Solar Energy  Energy Consumption  Energy Demand  Time Series  Real-time Electricity Rate  Periodic Functions  Q-function  Optimal Charging Strategy  Optimal Discharging Strategy  Optimal Idle Strategy  Numerical Analysis  
Parallel Driving in CPSS:A Unified Approach for Transport Automation and Vehicle Intelligence 期刊论文
IEEE, 2017, 卷号: 4, 期号: 4, 页码: 577-587
作者:  Fei-Yue Wang;  Nan-Ning Zheng;  Dongpu Cao;  Clara Marina Martinez;  Li Li;  Teng Liu
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Automation  Vehicles  Testing  Trajectory  Learning (Artificial Intelligence)  Road Transportation  
Imitating the Brain with Neurocomputer A “New” Way Towards Artificial General Intelligence 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 5, 页码: 520-531
作者:  Tie-Jun Huang
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Artificial general intelligence (AGI)  neuromorphic computing  neurocomputer  brain-like intelligence  imitationalism.  
Why Deep Neural Nets Cannot Ever Match Biological Intelligence and What To Do About It? 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 5, 页码: 532-541
作者:  Danko Nikolic
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Artificial intelligence  neural networks  strong artificial intelligence  practopoiesis, machine learning.