Optimal parameter identification of SOFC model using modified gray wolf optimization algorithm

Energy ◽  
2022 ◽  
Vol 240 ◽  
pp. 122800
Author(s):  
Jian Wang ◽  
Yi-Peng Xu ◽  
Chen She ◽  
Ping Xu ◽  
Hamid Asadi Bagal
Keyword(s):  
Parameter Identification ◽  
Optimization Algorithm ◽  
Optimal Parameter ◽  
Gray Wolf

Solve fractional differential equations via a hybrid method between variational iteration method and gray wolf optimization algorithm

2020 ◽  
pp. 2150144
Author(s):  
Ahmed Entesar ◽  
Omar Saber Qasim
Keyword(s):  
Differential Equations ◽  
Fractional Differential Equations ◽  
Hybrid Method ◽  
Optimization Algorithm ◽  
Iteration Method ◽  
Optimal Parameter ◽  
Variational Iteration Method ◽  
Gray Wolf ◽  
Variational Iteration ◽  
Fractional Differential

In this paper, a hybrid method between Variational Iteration Method (VIM) and gray wolf optimization algorithm (GWO) was proposed to solve the fractional differential equations (FDE), where the optimal parameter value ([Formula: see text] for the VIM was estimated by the GWO. The solutions in the proposed method, GWO-VIM, demonstrated the efficiency and reliability compared to the default method VIM, by calculating the maximum absolute errors (MAE) and mean square error (MSE).

scholarly journals Parameter identification method of hydraulic automatic gauge control system based on chaotic wolf pack optimization algorithm

AIP Advances ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 055302
Author(s):  
Yong Zhu ◽  
Guangpeng Li ◽  
Shengnan Tang ◽  
Wanlu Jiang ◽  
Zhijian Zheng
Keyword(s):  
Control System ◽  
Parameter Identification ◽  
Optimization Algorithm ◽  
Identification Method ◽  
Automatic Gauge Control

scholarly journals A New “Good and Bad Groups-Based Optimizer” for Solving Various Optimization Problems

2021 ◽  
Vol 11 (10) ◽  
pp. 4382
Author(s):  
Ali Sadeghi ◽  
Sajjad Amiri Doumari ◽  
Mohammad Dehghani ◽  
Zeinab Montazeri ◽  
Pavel Trojovský ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Fitness Function ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Gray Wolf ◽  
Good Group ◽  
Good Ability ◽  
Whale Optimization

Optimization is the science that presents a solution among the available solutions considering an optimization problem’s limitations. Optimization algorithms have been introduced as efficient tools for solving optimization problems. These algorithms are designed based on various natural phenomena, behavior, the lifestyle of living beings, physical laws, rules of games, etc. In this paper, a new optimization algorithm called the good and bad groups-based optimizer (GBGBO) is introduced to solve various optimization problems. In GBGBO, population members update under the influence of two groups named the good group and the bad group. The good group consists of a certain number of the population members with better fitness function than other members and the bad group consists of a number of the population members with worse fitness function than other members of the population. GBGBO is mathematically modeled and its performance in solving optimization problems was tested on a set of twenty-three different objective functions. In addition, for further analysis, the results obtained from the proposed algorithm were compared with eight optimization algorithms: genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), teaching–learning-based optimization (TLBO), gray wolf optimizer (GWO), and the whale optimization algorithm (WOA), tunicate swarm algorithm (TSA), and marine predators algorithm (MPA). The results show that the proposed GBGBO algorithm has a good ability to solve various optimization problems and is more competitive than other similar algorithms.

Optimal parameter identification strategy applied to lithium‐ion battery model

2021 ◽  
Author(s):  
Seydali Ferahtia ◽  
Ali Djeroui ◽  
Hegazy Rezk ◽  
Aissa Chouder ◽  
Azeddine Houari ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Lithium Ion Battery ◽  
Optimal Parameter ◽  
Lithium Ion ◽  
Battery Model ◽  
Identification Strategy
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