@inproceedings{f3363eb5dc3c4d40b527060f4ffa84c0,
title = "A damping factor based particle swarm optimization approach",
abstract = "This paper proposes a novel damping factor based particle swarm optimization (DFPSO) to solve the large scale and high-dimensional searching space problems in terms of convergence to global optima. In this optimal searching strategy, we balance the exploring and exploiting ability of particles by introducing a new damping factor. Also, fuzzy c-means clustering is applied to cluster the particles' positions for the individuals' neighborhood establishment. Our comparative study about benchmark test functions demonstrates that the proposed variant of PSO outweighs the performance of standard PSO and three state-of-Art variants of PSO in terms of global optimum convergence and final optimal results.",
keywords = "Damping Factor, Fuzzy C-Means Clustering, Particle Swarm Optimization",
author = "Mingfu He and Mingzhe Liu and Xin Jiang and Ruili Wang and Helen Zhou",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 9th International Conference on Modelling, Identification and Control, ICMIC 2017 ; Conference date: 10-07-2017 Through 12-07-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICMIC.2017.8321632",
language = "English",
series = "Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "13--18",
booktitle = "Proceedings of 2017 9th International Conference On Modelling, Identification and Control, ICMIC 2017",
address = "United States",
}