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Pollack Periodica
Authors:
Humam Kareem Jalghaf
,
Ali Habeeb Askar
,
Hazim Albedran
,
Endre Kovács
, and
Károly Jármai

Optimization (ALO) algorithm [ 8 ]. The behavior of the flocks of birds and fishes was the inspiration engine behind the Particle Swarm Optimization (PSO) algorithm, while the bee colony was the inspiration engine behind the Artificial Bee Colony (ABC) [ 9

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system using Particle Swarm Optimization (PSO) is introduced, which is implemented using Matlab. To solve a particle optimization problem, the number of particles is often set between 10 and 50. At first, the particle positions are - initialized randomly

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concrete retaining walls, optimization techniques are utilized, making retaining wall optimization essential for achieving economic efficiency [ 8 ]. In this work, Particle Swarm Optimization (PSO) [ 9 ], Grey Wolf Optimizer (GWO) [ 10 ], Artificial Bee

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] methods; this term can be defined as accumulative and shared knowledge among a group of individuals, and this kind of intelligence cannot be reached by one of them alone. Examples of swarm intelligence Particle Swarm Optimization (PSO) [ 6 ], Artificial

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active power is rescheduled to alleviate the congestion. Using the multi-objective Particle Swarm Optimization (PSO) algorithm, part-optimal solutions were introduced by Hazara and Sinha [ 3 ] to minimize overloads and lower operating costs. Balaraman et

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by congestion [ 6 ]. Nodal pricing, FACTS-based CM, ATC-based CM, and price area CM methods are coming under conventional CM methods. The computational time is more in Conventional CM methods compared to heuristic optimization methods. PSO, GA, BFA

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Pollack Periodica
Authors:
Ali Kareem Abdulrazzaq
,
György Bognár
, and
Balázs Plesz

. This paper uses the particle swarm optimization algorithm to solve this equation and determine the five parameters. PSO is one of the well-regarded algorithms in the literature for optimization tasks and is widely used in both science and industry. PSO

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changing solar irradiation and partial shade [ 3 ]. The literature has reviewed evolutionary algorithms Adaptive Neuro-Fuzzy Inference System (ANFIS-MPPT), Particle Swarm Optimization (PSO) differential evolution algorithm, Firefly Algorithm (FA) and

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Journal of Thermal Analysis and Calorimetry
Authors:
Rogério L. Pagano
,
Verônica M. A. Calado
,
Frederico W. Tavares
, and
Evaristo C. Biscaia

, the Particle Swarm Optimization (PSO) [ 1 ] has been extensively applied in parameter estimation. One important detail of these algorithms is that the knowledge of the objective function gradients and the initial parameter guesses are not necessary

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], particle swarm optimization (PSO) [ 20 ], and Grey-wolf optimization [ 21 ] are examples of common optimization methods that are given and used in exoskeleton devices. Algorithm for ant colony optimization [ 22 ] was also used. GA is easy to use and capable

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