An archive based particle swarm optimisation for feature selection in classification

Xue, B, Qin, K and Zhange, M 2014, 'An archive based particle swarm optimisation for feature selection in classification', in Derong Liu (ed.) Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2014), Beijing, China, 6 -11 July 2014, pp. 3119-3126.


Document type: Conference Paper
Collection: Conference Papers

Title An archive based particle swarm optimisation for feature selection in classification
Author(s) Xue, B
Qin, K
Zhange, M
Year 2014
Conference name 2014 IEEE Congress on Evolutionary Computation (CEC)
Conference location Beijing, China
Conference dates 6 -11 July 2014
Proceedings title Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2014)
Editor(s) Derong Liu
Publisher IEEE
Place of publication United States
Start page 3119
End page 3126
Total pages 8
Abstract Although various population initialization techniques have been employed in evolutionary algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap and attract more attentions from EA researchers to this crucial yet less explored area, we conduct a systematic review of the existing population initialization techniques. Specifically, we categorize initialization techniques from three exclusive perspectives, i.e., randomness, compositionality and generality. Characteristics of the techniques belonging to each category are carefully analysed to further lead to several sub-categories. We also discuss several open issues related to this research topic, which demands further in-depth investigations.
Subjects Neural, Evolutionary and Fuzzy Computation
Pattern Recognition and Data Mining
Keyword(s) Algorithms Compositionality
Evolutionary algorithms (EAs)
Initialization technique
Population initializations
Research topics
Systematic Review
DOI - identifier 10.1109/CEC.2014.6900472
Copyright notice ©2014 IEEE
ISBN 9781479966264
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
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