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New Technology of Library and Information Service  2015, Vol. 31 Issue (9): 46-51    DOI: 10.11925/infotech.1003-3513.2015.09.07
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Fuzzy Classification Method Based on Particle Swarm Optimization and Fuzzy Comprehensive Evaluation
Yin Xihong, Qiao Xiaodong, Zhang Yunliang, Li Guoshuang
Institute of Scientific & Technical Information of China, Beijing 100038, China
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[Objective] Solve the problem of rigid division of the traditional classification and some classification methods only dealing with discrete data. [Methods] The fuzzy comprehensive evaluation method is put forward to realize the fuzzy classification for continuous attributes samples, obtaining the soft classification of samples to categories. In the process, the method of continuous attributes discretization is used to divide attribute interval, and the particle swarm optimization algorithm is used to obtain the optimal weight distribution. The final results are the membership degrees of samples to each category. [Results] This method can effectively achieve the soft division of samples. [Limitations] This method is difficult to divide the attribute whose values is too concentrated. [Conclusions] This fuzzy classification method based on particle swarm optimization and fuzzy comprehensive evaluation is effective and feasible.

Received: 05 May 2015      Published: 06 April 2016
:  TP18  

Cite this article:

Yin Xihong, Qiao Xiaodong, Zhang Yunliang, Li Guoshuang. Fuzzy Classification Method Based on Particle Swarm Optimization and Fuzzy Comprehensive Evaluation. New Technology of Library and Information Service, 2015, 31(9): 46-51.

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