Identification of λ-fuzzy measure by modified genetic algorithms

Authors:
Chuanjun Zhu;Yurong Chen;Xinhai Lu;Chaoyong Zhang
Affiliations:
Huazhong University of Science and Technology, Research Center for Land Resource and Real Estate, Wuhan, China and Department of Mechanical Engineering, Hubei Automotive Industries Institute, Shiy ...;Department of Mechanical Engineering, Hubei Automotive Industries Institute, Shiyan, China;Huazhong University of Science and Technology, Research Center for Land Resource and Real Estate, Wuhan, China;School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
Year:
2009

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Abstract

Fuzzy measure is subjective scale for the degrees of fuzziness and suitable for analyzing human subjective evaluation processes. It is not easy to provide consistent fuzzy measure values with fuzzy measure properties since they have to be subjective determined. Thus it induces an identification problem that determines measure values with fuzzy measure properties from human-provided. The λ-fuzzy measure is a typical fuzzy measure widely used. Although several studies have been made on λ-fuzzy measure identification, the corresponding computation process is rather complicated and the result is not ideal. In this paper, we introduce a method for identification of λ-fuzzy measures from data set. It is implemented by using modified genetic algorithm and example data is tested, the result shows its applicability.