Optimization of energy management and conversion in the water systems based on evolutionary algorithms-Reference-Cited by-同舟云学术

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Optimization of energy management and conversion in the water systems based on evolutionary algorithms

Published:2018-03-09 Issue:10 Volume:31 Page:5951-5964
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Karami Hojat,Ehteram Mohammad,Mousavi Sayed-Farhad,Farzin Saeed,Kisi Ozgur,El-Shafie Ahmed

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/content/pdf/10.1007/s00521-018-3412-6.pdf

Reference28 articles.

1. Afsahr A, Sharifi M, Bozorg-Hadad O (2011) Optimizing multi reservoir operation rules: an improved HBMO. J Hydroinf 13(1):121–139

2. Afshar MH (2013) A cellular automata approach for the hydro-power operation of multi-reservoir systems. J Proc ICE Water Manage 166(9):465–478

3. Ahmed JA, Sarma AK (2005) Genetic algorithm for optimal operation policy of a multi-purpose reservoir. Water Resour Manag 19(2):145–161

4. Brambilla M, Fontes AS, Medeiros YDP (2017) Cost-benefit analysis of reservoir operation scenarios considering environmental flows for the lower stretch of the São Francisco River (Brazil). RBRH 22:34–41

5. Li Y, Cui Q, Li C, Wang X, Cai Y, Cui G, Yang Z (2017) An improved multi-objective optimization model for supporting reservoir operation of China’s South-to-North Water Diversion Project. Sci Total Environ 575:970–981

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