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bibtex-reference |
@INPROCEEDINGS{Zheng2003,
author={Yong-ling Zheng and Long-Hua Ma and Li-yan Zhang and Ji-xin Qian},
booktitle={Machine Learning and Cybernetics, 2003 International Conference on},
title={On the convergence analysis and parameter selection in particle swarm optimization},
year={2003},
volume={3},
pages={1802-1807 Vol.3},
abstract={A PSO with increasing inertia weight, distinct from a widely used PSO with decreasing inertia weight, is proposed in this paper. Far from drawing conclusions from sole empirical study or rule of thumb, this algorithm is derived from particle trajectory study and convergence analysis. Four standard test functions are used to confirm its validity finally. From the experiments, it is clear that a PSO with increasing inertia weight outperforms the one with decreasing inertia weight, both in convergent speed and solution precision, with no additional computing load.},
keywords={convergence;optimisation;search problems;convergence analysis;inertia weight;parameter selection;particle swarm optimization;particle trajectory study;thumb rule;Algorithm design and analysis;Birds;Control systems;Convergence;Engineering drawings;Equations;Particle swarm optimization;Systems engineering and theory;Testing;Thumb},
doi={10.1109/ICMLC.2003.1259789},} |
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standard-reference |
Y. Zheng, L. Ma, L. Zhang, J. Qian, On the convergence analysis and parameter selection in particle swarm optimization, in: Proceedings of the International Conference on Machine Learning and Cybernetics, 2003, pp. 1802Ð1807. |