DocumentCode :
2042375
Title :
Data clustering algorithms based on Swarm Intelligence
Author :
Bharne, Pankaj K. ; Gulhane, V.S. ; Yewale, Shweta K.
Author_Institution :
Sipna Coll. of Eng. & Tech., Amravati, India
Volume :
4
fYear :
2011
fDate :
8-10 April 2011
Firstpage :
407
Lastpage :
411
Abstract :
For a decade swarm Intelligence, an artificial intelligence discipline, is concerned with the design of intelligent multi-agent systems by taking inspiration from the collective behaviors of social insects and other animal societies. Swarm Intelligence is a successful paradigm for the algorithm with complex problems. This paper focuses on the procedure of most successful methods of optimization techniques inspired by Swarm Intelligence: Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). This paper also gives a comparative analysis of PSO and ACO for data clustering.
Keywords :
artificial intelligence; multi-agent systems; particle swarm optimisation; pattern clustering; ACO; PSO; ant colony optimization; artificial intelligence; data clustering algorithm; intelligent multiagent system; particle swarm optimization; social insect; swarm intelligence; Algorithm design and analysis; Ant colony optimization; Clustering algorithms; Genetic algorithms; Optimization; Particle swarm optimization; Signal processing algorithms; Comparison of Data Clustering Algorithms; Data Clustering; Data Clustering Algorithms Based on swarm Intelligence; Swarm Intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics Computer Technology (ICECT), 2011 3rd International Conference on
Conference_Location :
Kanyakumari
Print_ISBN :
978-1-4244-8678-6
Electronic_ISBN :
978-1-4244-8679-3
Type :
conf
DOI :
10.1109/ICECTECH.2011.5941931
Filename :
5941931
Link To Document :
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