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Deep swarm: Nested particle swarm optimization [PDF]
, 2017 A new generation of particle swarm optimization (PSO) has been developed that automatically evolves optimal or near-optimal values for parameters of the PSO algorithm such as population size and neighborhood size, and, if used, parameters of associated ...
Eberhart, Russell C. +2 more
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Feedback learning particle swarm optimization [PDF]
, 2011 This is the author’s version of a work that was accepted for publication in Applied Soft Computing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may ...
Andrews +34 more
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Particle Swarm Optimization (PSO) Based Turbine Control
Intelligent Control and Automation, 2013 The steam turbine control system is strongly non-linear in all operating conditions. Proportional-Integral-Derivative (PID) controller that is currently used in control systems of many types of equipment is not considered highly precision for turbine speed control system.
Ali Tarique, Hossam A. Gabbar
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A Novel TSA-PSO Based Hybrid Algorithm for GMPP Tracking under Partial Shading Conditions
Energies, 2022 In this paper, a new hybrid TSA-PSO algorithm is proposed that combines tunicate swarm algorithm (TSA) with the particle swarm optimization (PSO) technique for efficient maximum power extraction from a photovoltaic (PV) system subjected to partial ...
Abhishek Sharma +5 more
doaj +1 more source
A particle swarm optimization based memetic algorithm for dynamic optimization problems [PDF]
, 2009 Copyright @ Springer Science + Business Media B.V. 2010.Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic.
AS Uyar +25 more
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A Modified NM-PSO Method for Parameter Estimation Problems of Models
Journal of Applied Mathematics, 2012 Ordinary differential equations usefully describe the behavior of a wide range of dynamic physical systems. The particle swarm optimization (PSO) method has been considered an effective tool for solving the engineering optimization problems for ordinary ...
An Liu, Erwie Zahara, Ming-Ta Yang
doaj +1 more source
IEEE Access, 2020 An explosion field is random and nonuniform, and test sensors can be damaged by fragments during blast wave monitoring. When accurately and comprehensively obtaining the experimental data and the dynamic distributions from an explosion field, the ...
Yong-Hong Ding, Wen-Bin You
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The Butterfly-Particle Swarm Optimization (Butterfly-PSO/BF-PSO) Technique and Its Variables [PDF]
SSRN Electronic Journal, 2015 The new presented Butterfly-PSO technique (or BF-PSO) is basically originated by Particle Swarm Optimization (PSO). The Butterfly-PSO technique (BF-PSO) appears as a new growing star among all optimization techniques. The proposed 'Butterfly- Particle Swarm Optimization (Butterfly or BF-PSO)' is inspired by butterfly natural intelligence, character ...
Aashish Kumar Bohre +2 more
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Controller design for synchronization of an array of delayed neural networks using a controllable [PDF]
, 2011 This is the post-print version of the Article - Copyright @ 2011 ElsevierIn this paper, a controllable probabilistic particle swarm optimization (CPPSO) algorithm is introduced based on Bernoulli stochastic variables and a competitive penalized method ...
Cao +36 more
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Novel Artificial Human Optimization Field Algorithms - The Beginning
, 2019 New Artificial Human Optimization (AHO) Field Algorithms can be created from scratch or by adding the concept of Artificial Humans into other existing Optimization Algorithms.
Gajawada, Satish, Mustafa, Hassan
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