Comparative Study of Particle Swarm Optimization Algorithms in Solving Size, Topology, and Shape Optimization

Journal of Physics Conference Series ◽

10.1088/1742-6596/1625/1/012015 ◽

2020 ◽

Vol 1625 ◽

pp. 012015

Author(s):

K Harsono ◽

D Prayogo ◽

K E Prasetyo ◽

F T Wong ◽

D Tjandra

Keyword(s):

Particle Swarm Optimization ◽

Comparative Study ◽

Shape Optimization ◽

Optimization Algorithms ◽

Particle Swarm ◽

Swarm Optimization ◽

Topology And Shape Optimization

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Improve Linear Quadratic Regulator by Particle Swarm Optimization Algorithms for Two Wheeled Self Bala ncing Mobile robot

Iraqi Journal for Electrical And Electronic Engineering ◽

10.33762/eeej.2017.135280 ◽

2017 ◽

Vol 13 (2) ◽

pp. 173-179

Author(s):

A Noor.M.Mjeed ◽

A Ekhlas.H.Karam

Keyword(s):

Particle Swarm Optimization ◽

Mobile Robot ◽

Optimization Algorithms ◽

Particle Swarm ◽

Linear Quadratic Regulator ◽

Linear Quadratic ◽

Swarm Optimization

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Application of BPNN optimized by chaotic adaptive gravity search and particle swarm optimization algorithms for fault diagnosis of electrical machine drive system

Electrical Engineering ◽

10.1007/s00202-021-01335-0 ◽

2021 ◽

Author(s):

Peng Zhang ◽

Zhiwei Cui ◽

Yinjiang Wang ◽

Shichuan Ding

Keyword(s):

Particle Swarm Optimization ◽

Fault Diagnosis ◽

Optimization Algorithms ◽

Particle Swarm ◽

Drive System ◽

Electrical Machine ◽

Swarm Optimization ◽

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An optimization-based control of indoor lighting: A comparative study between Particle Swarm Optimization and Firefly Algorithm

2021 IEEE International Conference in Power Engineering Application (ICPEA) ◽

10.1109/icpea51500.2021.9417753 ◽

2021 ◽

Author(s):

Nik Sahidah Nik Ahmad ◽

Nur Hanis Mohammad Radzi ◽

Mohd Noor Abdullah ◽

Khairul Rijal Wagiman ◽

Muhammad Nafis Ismail ◽

...

Keyword(s):

Particle Swarm Optimization ◽

Comparative Study ◽

Firefly Algorithm ◽

Particle Swarm ◽

Swarm Optimization ◽

Indoor Lighting

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Shape optimization of GFRP elastic gridshells by the weighted Lagrange ε-twin support vector machine and multi-objective particle swarm optimization algorithm considering structural weight

10.1016/j.istruc.2021.05.077 ◽

2021 ◽

Vol 33 ◽

pp. 2066-2084

Author(s):

Soheila Kookalani ◽

Bin Cheng ◽

Sheng Xiang

Keyword(s):

Support Vector Machine ◽

Particle Swarm Optimization ◽

Shape Optimization ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Particle Swarm ◽

Twin Support Vector Machine ◽

Support Vector ◽

Swarm Optimization ◽

Multi Objective

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Decision Space Scalability Analysis of Multi-Objective Particle Swarm Optimization Algorithms

2021 IEEE Congress on Evolutionary Computation (CEC) ◽

10.1109/cec45853.2021.9504846 ◽

2021 ◽

Author(s):

Amirali Madani ◽

Beatrice Ombuki-Berman ◽

Andries Engelbrecht

Keyword(s):

Particle Swarm Optimization ◽

Optimization Algorithms ◽

Particle Swarm ◽

Decision Space ◽

Swarm Optimization ◽

Multi Objective ◽

Scalability Analysis

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Developing a Decision Model Based on Decision Tree and Particle Swarm Optimization Algorithms to Identify Optimal Locations for Solar Power Plants Construction in Iran

SSRN Electronic Journal ◽

10.2139/ssrn.3900348 ◽

2021 ◽

Author(s):

Saman Nadizadeh Shorabeh ◽

Najmeh Neysani Samani ◽

Foad Minaei ◽

Hamzeh Karimi Firozjaei ◽

Mehdi Homaee ◽

...

Keyword(s):

Particle Swarm Optimization ◽

Decision Tree ◽

Decision Model ◽

Power Plants ◽

Solar Power ◽

Optimization Algorithms ◽

Particle Swarm ◽

Swarm Optimization ◽

Model Based ◽

Solar Power Plants

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A review on particle swarm optimization algorithms and their applications to data clustering

Artificial Intelligence Review ◽

10.1007/s10462-010-9191-9 ◽

2010 ◽

Vol 35 (3) ◽

pp. 211-222 ◽

Author(s):

Sandeep Rana ◽

Sanjay Jasola ◽

Rajesh Kumar

Keyword(s):

Particle Swarm Optimization ◽

Data Clustering ◽

Optimization Algorithms ◽

Particle Swarm ◽

Swarm Optimization

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Constrained path planning of autonomous underwater vehicle using selectively-hybridized particle swarm optimization algorithms

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2019.12.326 ◽

2019 ◽

Vol 52 (21) ◽

pp. 315-322 ◽

Author(s):

Hui Sheng Lim ◽

Shuangshuang Fan ◽

Christopher K.H. Chin ◽

Shuhong Chai ◽

Neil Bose ◽

...

Keyword(s):

Particle Swarm Optimization ◽

Path Planning ◽

Autonomous Underwater Vehicle ◽

Optimization Algorithms ◽

Particle Swarm ◽

Underwater Vehicle ◽

Swarm Optimization

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Evaluation of Differential Evolution and Particle Swarm Optimization Algorithms at Training of Neural Network for prediction

IJCI. International Journal of Computers and Information ◽

10.21608/ijci.2014.33964 ◽

2014 ◽

Vol 3 (1) ◽

pp. 2-14

Author(s):

Mustafa Abdelsalam ◽

Hatem Ahmed ◽

W. Abdulwahed

Keyword(s):

Neural Network ◽

Particle Swarm Optimization ◽

Differential Evolution ◽

Optimization Algorithms ◽

Particle Swarm ◽

Swarm Optimization

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Anti-synchronization of discrete-time chaotic systems using optimization algorithms

International Journal of Electronics Signals and Systems ◽

10.47893/ijess.2011.1028 ◽

2011 ◽

pp. 143-147

Author(s):

Mahdieh Adeli ◽

Hassan Zarabadipoor

Keyword(s):

Particle Swarm Optimization ◽

Pid Control ◽

Pid Controller ◽

Chaotic Systems ◽

Optimization Algorithms ◽

Particle Swarm ◽

Optimization Methods ◽

Swarm Optimization ◽

Improved Particle Swarm Optimization ◽

Modified Particle Swarm Optimization

In this paper, anti-synchronization of discrete chaotic system based on optimization algorithms are investigated. Different controllers have been used for anti-synchronization of two identical discrete chaotic systems. A proportional-integral-derivative (PID) control is used and its parameters is tuned by the four optimization algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO), modified particle swarm optimization (MPSO) and improved particle swarm optimization (IPSO). Simulation results of these optimization methods to determine the PID controller parameters to anti-synchronization of two chaotic systems are compared. Numerical results show that the improved particle swarm optimization has the best result.

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