Analysis of Particle Swarm Optimization Algorithm

By Qinghai Bai. Computer and Information Science, 2010

911 citations recorded by the source corpus.

Particle swarm optimization is a heuristic global optimization method and also an optimization algorithm, which is based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. The algorithm is widely used and rapidly developed for its easy implementation and few particles required to be tuned. The main idea of the principle of PSO is presented; the advantages and the shortcomings are summarized. At last this paper presents some kinds of improved versions of PSO and research situation, and the future research issues are also given.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/6d007fd5f734cb4c6c9457e22f46a58be5edb662

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Citations in the corpus

Comparative study between Differential Evolution and Particle Swarm Optimization algorithms in training of feed-forward neural network for stock price prediction (2010, background): “Particle Swarm Optimization (PSO) is proposed algorithm by James Kennedy and Russell Eberhart in 1995, motivated by social behavior of organisms such as bird flocking and fish schooling [6].”
Network intrusion detection system: A systematic study of machine learning and deep learning approaches (2020, methodology): “Ali et al 79 addressed the IDS problem by proposing a model based on FLN and particle swarm optimization 80 (PSO-FLN) and tested the model using KDD Cup’99 dataset.”
Particle Swarm Optimization: Technique, System and Challenges (2011, background): “In analysis, PSO has advantages and disadvantages [4].”
Moth–flame optimization algorithm: variants and applications (2019, background): “…[37] Balance between [87] Deal with the complexﬁtnesslandscape [16] Don’t have overlappingandmutationcalculation[15] Increases the diversity of the new solutions [77] at [66] Weaknesses [56] Trapped in a local optimum [113] Evaluation is [140] Suffers from [15]…”
A Machine Learning Model for Stock Market Prediction (2014, methodology): “PSO is a recently proposed algorithm by James Kennedy and Russell Eberhart in 1995, motivated by social behavior of organisms such as bird flocking and fish schooling [8].”
Modeling groundwater fluctuations by three different evolutionary neural network techniques using hydroclimatic data (2017, background): “The number of the dimension is equivalent to the constant of the solution (Bai 2010).”