Multi-Sub-Swarm PSO Classifier Design and Rule Extraction

DOI

10.2991/ccis-13.2013.25How to use a DOI?

Keywords

multi-sub-swarm PSO; classifier; gas emission concentration; rule extraction

Abstract

In this paper, a new classifier, based on multi-sub-swarm PSO algorithm, is proposed. Natural number coding is used in the classifier to avoid the updating inconvenience of binary encoding that has different properties dimensions. Classification is done by parallel search of multi-sub-swarm PSO algorithm. According to the characteristics of the coal mine gas emission concentration data, an extraction model is constructed of classification rules of coal gas emission concentration. The results showed that this classifier have high prediction accuracy rate, and the gas emission concentration rules, extracted from its rule space using this classifier, run efficiency significantly with less redundancy.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chang Yanwei
AU  - Yu Guofang
PY  - 2013/11
DA  - 2013/11
TI  - Multi-Sub-Swarm PSO Classifier Design and Rule Extraction
BT  - Proceedings of the The 1st International Workshop on Cloud Computing and Information Security
PB  - Atlantis Press
SP  - 104
EP  - 107
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccis-13.2013.25
DO  - 10.2991/ccis-13.2013.25
ID  - Yanwei2013/11
ER  -