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American Journal of Water Resources. 2020, 8(3), 118-127
DOI: 10.12691/AJWR-8-3-2
Original Research

Enhancing Artificial Neural Network with Multi-Objective Evolutionary Algorithm for Optimizing Real Time Reservoir Operations: A Review

Ajala Abiodun Ladanu1, , Semiu Akanmu2 and Josiah Adeyemo3

1Department of Mechanical Engineering, The Polytechnic Ibadan, Nigeria

2North Dakota State University, United States

3University of Washington, Seattle Campus, United States

Pub. Date: May 20, 2020
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Cite this paper

Ajala Abiodun Ladanu, Semiu Akanmu and Josiah Adeyemo. Enhancing Artificial Neural Network with Multi-Objective Evolutionary Algorithm for Optimizing Real Time Reservoir Operations: A Review. American Journal of Water Resources. 2020; 8(3):118-127. doi: 10.12691/AJWR-8-3-2

Abstract

The need for, and the process of, optimizing real time reservoir operations have attracted substantial research attention. Among these is the employment of artificial neural network (ANN), singly or with supporting algorithms, for real time multi-objective reservoir operation optimization. Using Systematic Literature Review (SLR), this paper reviews 66 studies, comprising of studies that employed ANN with or without another training algorithm(s), and those that employed evolutionary algorithm (EA) of any type for real time reservoir operations optimization. From this, it highlights the necessity of using ANN and the suitability of EA as a training algorithm. This paper, from the meta-analysis of the studies reviewed, shows that, though ANN is primarily suitable for real time forecasting, the best network architecture is the real-time recurrent learning (RTRL) neural network algorithm. And, ANN supported with supervised or unsupervised learning algorithm, has better performance potential than those singly used. Also, evolutionary algorithms are presented as viable supporting training algorithms capable of extrapolating data of deeper abstraction, complex uncertainty, with consistent predictive capacities.

Keywords

artificial neural network, evolutionary algorithm, multi-objective framework, real time optimization, systematic literature review

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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