A self-tuning ANN model for simulation and forecasting of surface flows-Reference-Cited by-同舟云学术

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A self-tuning ANN model for simulation and forecasting of surface flows

Published:2016-04-19 Issue:9 Volume:30 Page:2907-2929
ISSN:0920-4741
Container-title:Water Resources Management
language:en
Short-container-title:Water Resour Manage

Author:

Bozorg-Haddad Omid,Zarezadeh-Mehrizi Mahboubeh,Abdi-Dehkordi Mehri,Loáiciga Hugo A.,Mariño Miguel A.

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11269-016-1301-2.pdf

Reference41 articles.

1. Ahmad AL, Azid IA, Yusof AR, Seetharamu KN (2004) Emission control in palm oil mills using artificial neural network and genetic algorithm. J Comput Chem Eng 28(12):2709–2715

2. Ahmadi M, Bozorg-Haddad O, Mariño MA (2014) Extraction of flexible multi-objective real-time reservoir operation rules. Water Resour Manag 28(1):131–147

3. Ashofteh P-S, Bozorg-Haddad O, Mariño MA (2013a) Climate change impact on reservoir performance indices in agricultural water supply. J Irrig Drain Eng 139(2):85–97

4. Ashofteh P-S, Bozorg-Haddad O, Mariño MA (2013b) Scenario assessment of streamflow simulation and its transition probability in future periods under climate change. Water Resour Manag 27(1):255–274

5. Ashofteh PS, Bozorg-Haddad O, Loáiciga HA (2015a) Evaluation of climatic-change impacts on multi-objective reservoir operation with multiobjective genetic programming. J Water Resour Plann Manag 141(11). doi: 10.1061/(ASCE)WR.1943-5452.0000540

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