Single- and multi-objective particle swarm optimization of reservoir structure in Echo State Network

Chouikhi, Naima; Fdhila, Raja; Ammar, Boudour; Rokbani, Nizar; Alimi, Adel M.

doi:10.1109/ijcnn.2016.7727232

Cited by 19 publications

(15 citation statements)

References 19 publications

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“…A meta-heuristic algorithm performs two major searches in the problem space: a global search is performed to obtain multiple solutions and local searches in the neighborhoods of the existing solutions [61,62]. This allows improvement to be made in the obtained solutions.…”

Section: Exploration and Exploitationmentioning

confidence: 99%

Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms

et al. 2021

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In engineering and scientific disciplines, there are extensive Optimization Application Problems (OAPs) such as economic dispatch, structural design, and water resources. One of the major OAPs is the operation of dams and reservoirs to minimize the gap between water supply for irrigation and demand patterns such as hydropower generation. Drawing optimal operation for dams and reservoirs is often categorized as discontinuity, multimodality, non-differentiability and nonconvexity. Classical mathematical programming-based methods for optimization might be inappropriate or unrealizable in drawing optimal operation rules for dam and reservoir operation. During the last two decades, new optimization methodsbased on nature-inspired meta-heuristic algorithms (MHAs) have motivated hydrologists to investigate MHAs as better alternative optimization tools for identifying the optimal dam and reservoir operation rules. To solve the dam and reservoir-optimization applications better, this review presents the past, present, and prospective research directions using MHAs. The problem of dam and reservoir optimization requires a fundamental shift of focus towards enhancing not only the problem formulation and decomposition but also the computational efficiency of MHAs.

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Section: Exploration and Exploitationmentioning

confidence: 99%

Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms

et al. 2021

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“…It is dynamic and has strong dependencies. As it is coupled with high degree of confusion, it is difficult for predication [31]. It can be described by…”

Section: Synthetic Datamentioning

confidence: 99%

An echo state network architecture based on quantum logic gate and its optimization

et al. 2020

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“…Concerning optimization tasks, there are many useful techniques, such as evolutionary computation (Chouikhi et al, 2016), global optimization, naive optimization, etc.…”

Section: The Selector Componentmentioning

confidence: 99%

BrainOS: A Novel Artificial Brain-Alike Automatic Machine Learning Framework

Howard

Chouikhi

Adeel

et al. 2020

Front. Comput. Neurosci.

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Single- and multi-objective particle swarm optimization of reservoir structure in Echo State Network

Cited by 19 publications

References 19 publications

Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms

Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms

An echo state network architecture based on quantum logic gate and its optimization

BrainOS: A Novel Artificial Brain-Alike Automatic Machine Learning Framework

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