Neural Networks and Reinforcement Learning in Control of Water Systems-Reference-Cited by-同舟云学术

Neural Networks and Reinforcement Learning in Control of Water Systems

Published:2003-11 Issue:6 Volume:129 Page:458-465
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Bhattacharya B.¹,Lobbrecht A. H.²,Solomatine D. P.³

Affiliation:

1. Research Fellow, Hydroinformatics, International Institute for Infrastructural, Hydraulic and Environmental Engineering, P.O. Box 3015, 2601 DA Delft, The Netherlands.

2. Senior Lecturer in Hydroinformatics, International Institute for Infrastructural, Hydraulic and Environmental Engineering, P.O. Box 3015, 2601 DA Delft, The Netherlands and HydroLogic BV, P.O. Box 2177, 3800 CD Amersfoort, The Netherlands.

3. Associate Professor in Hydroinformatics, International Institute for Infrastructural, Hydraulic and Environmental Engineering, P.O. Box 3015, 2601 DA Delft, The Netherlands.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-9496%282003%29129%3A6%28458%29

Reference21 articles.

1. Bhattacharya B. and Solomatine D. P. (2000). “Application of artificial neural network in stage-discharge relationship.” Proc. Hydroinformatics Conf. 2000 .

2. Crites R. H. and Barto A. G. (1996). “Improving elevator performance using reinforcement learning.” Advances in Neural Information Processing Systems Proc. 1995 Conf. MIT Press Cambridge Mass.

3. An artificial neural network approach to rainfall-runoff modelling

4. Harris C. J. (1994). Advances in intelligent control Taylor and Francis London.

5. Haykin S. (1999). Neural networks: A comprehensive foundation Prentice-Hall Upper Saddle River N.J.

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