@inproceedings{acede9f7ae6544fe8f61a6d8866429f4,
title = "An adaptive tribe-particle swarm optimization",
abstract = "This paper talks about the problems in particle swarm optimization (PSO), including local optimum and difficulty in improving solution accuracy by fine tuning. We presents a new variation of Adaptive Tribe-PSO model where nonlinear updating of inertia weight and a particle's fitness with Tribe-PSO model are combined to improve the speed of convergence as well as fine tune the search in the multidimensional space. The method proved to be a powerful global optimization algorithm. {\textcopyright} 2011 Springer-Verlag.",
keywords = "accuracy, adaptive weight, local optimum, tribe particle swarm optimization",
author = "SONG, \{Yong Duan\} and Lu ZHANG and Peng HAN",
year = "2011",
month = jun,
day = "14",
doi = "10.1007/978-3-642-21515-5\_11",
language = "English",
isbn = "9783642215148",
series = "Lecture Notes in Computer Science",
publisher = "Springer Berlin Heidelberg",
pages = "86--92",
editor = "Ying TAN and Yuhui SHI and Yi CHAI and Guoyin WANG",
booktitle = "Advances in Swarm Intelligence: Second International Conference, ICSI 2011, Proceedings",
}