Evolutionary shuffled frog leaping with memory pool for parameter optimization
Yun Liu,Ali Asghar Heidari,Xiaojia Ye,Chen Chi,Xuehua Zhao,Chao Ma,Hamza Turabieh,Huiling Chen,Rongrong Le +8 more
TLDR
SFLBS has considerable accuracy in extracting the unknown parameters of the PV system problem, and its convergence speed is satisfactory, and SFLBS is used to evaluate three commercial PV modules under different irradiance and temperature conditions.About:
This article is published in Energy Reports.The article was published on 2021-11-01 and is currently open access. It has received 31 citations till now. The article focuses on the topics: Population & Crossover.read more
Citations
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Boosting slime mould algorithm for parameter identification of photovoltaic models
TL;DR: Simulation results demonstrate that a developed SMA-based method can accurately extract the unknown photovoltaic solar cells' unknown parameters and achieve excellent convergence rapidity and stability performance.
Journal ArticleDOI
Simulated annealing-based dynamic step shuffled frog leaping algorithm: Optimal performance design and feature selection
Yun Liu,Ali Heidari,Zhennao Cai,Guoxi Liang,Huiling Chen,Zhifang Pan,Abdulmajeed Alsufyani,Sami Bourouis +7 more
TL;DR: In this article , an advanced shuffled frog leaping algorithm (DSSRLFLA) is developed for model evaluation and feature selection, which incorporates a dynamic step size adjustment strategy based on historical information, a specular reflection learning mechanism, and a simulated annealing mechanism based on chaotic mapping and levy flight.
Journal ArticleDOI
Identification of Solar Photovoltaic Model Parameters Using an Improved Gradient-Based Optimization Algorithm With Chaotic Drifts
M. Premkumar,Pradeep Jangir,C. Ramakrishnan,G. Nalinipriya,Hassan Haes Alhelou,B. Santhosh Kumar +5 more
TL;DR: In this article, the Chaotic-GBO (CGBO) algorithm is proposed to derive the parameters of PV modules while offering precise I-V and P-V curves.
Journal ArticleDOI
Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems
Ahmed R. Ginidi,Sherif M. Ghoneim,Abdallah M. Elsayed,Ragab A. El-Sehiemy,Abdullah M. Shaheen,Attia A. El-Fergany +5 more
TL;DR: A new implementation of the Gorilla Troops Optimization (GTO) technique for parameter extraction of several PV models is created and its efficacy and superiority are expressed by calculating the standard deviations of the fitness values, which indicates that the SD and DD models are smaller than 1E−16, and 1E −6, respectively.
Journal ArticleDOI
Random reselection particle swarm optimization for optimal design of solar photovoltaic modules
Huiling Chen,Yi Fan,Pengjun Wang,Ali Asghar Heidari,Huiling Chen,HamzaTurabieh,Majdi Mafarja +6 more
TL;DR: This paper proposes the PSOCS algorithm based on the core components of particle swarm optimization and the strategy of random reselection of parasitic nests that appeared in the cuckoo search and suggests that this new variant of PSO can be employed as a tool for the optimal designing of photovoltaic systems.
References
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Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
TL;DR: The comprehensive learning particle swarm optimizer (CLPSO) is presented, which uses a novel learning strategy whereby all other particles' historical best information is used to update a particle's velocity.
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Harris hawks optimization: Algorithm and applications
Ali Asghar Heidari,Ali Asghar Heidari,Seyedali Mirjalili,Hossam Faris,Ibrahim Aljarah,Majdi Mafarja,Huiling Chen +6 more
TL;DR: The statistical results and comparisons show that the HHO algorithm provides very promising and occasionally competitive results compared to well-established metaheuristic techniques.
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Slime mould algorithm: A new method for stochastic optimization
Shimin Li,Huiling Chen,Mingjing Wang,Ali Asghar Heidari,Ali Asghar Heidari,Seyedali Mirjalili +5 more
TL;DR: The proposed slime mould algorithm has several new features with a unique mathematical model that uses adaptive weights to simulate the process of producing positive and negative feedback of the propagation wave of slime mould based on bio-oscillator to form the optimal path for connecting food with excellent exploratory ability and exploitation propensity.
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Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization
TL;DR: Experimental results in terms of the likelihood of convergence to a global optimal solution and the solution speed suggest that the SFLA can be an effective tool for solving combinatorial optimization problems.
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Backtracking Search Optimization Algorithm for numerical optimization problems
TL;DR: The Wilcoxon Signed-Rank Test is used to statistically compare BSA's effectiveness in solving numerical optimization problems with the performances of six widely used EA algorithms: PSO, CMAES, ABC, JDE, CLPSO and SADE and shows that in general, BSA can solve the benchmark problems more successfully than the comparison algorithms.