Accession number:20100712709651
Title: Choquet integral with respect to extensional L-measure and its application
Authors: Liu, Hsiang-Chuan (1); Chen, Chin-Chun (2); Jheng, Yu-Du (2); Chien, Maw-Fa (4)
Author affiliation:(1) Department of Bioinformatics, Asia University, Taiwan; (2) Graduate Institute of Educational Measurement and Statistics, Taichung University, Taichung, Taiwan; (3) Department of General Education, Min-Hwei College, Taiwan; (4) College Entrance Examination Center, Taiwan
Corresponding author:Liu, H.-C.
Source title: 6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Abbreviated source title:Int. Conf. Fuzzy Syst. Knowl. Discov., FSKD Volume:6
Monograph title:6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Issue date:2009
Publication year:2009 Pages:131-136
Article number:5359812 Language:English
ISBN-13:9780769537351
Document type:Conference article (CA)
Conference name:6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Conference date:August 14, 2009 - August 16, 2009 Conference location:Tianjin, China
Conference code:79367
Sponsor:Tianjin University of Technology
Publisher:IEEE Computer Society, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
Abstract:The well known fuzzy measures, γ-measure and P- measure, have only one formulaic solution. An multivalent fuzzy measure with infinitely many solutions of closed form based on P- measure was proposed by our previous work, called L-measure, In
this paper, A further improved fuzzy measure, called extensional L- measure, is proposed. This new fuzzy measure is proved that it is not only an extension of L-measure but also can be considered as an extension of the γ-measure and P-measure. For evaluating the Choquet integral regression models with our proposed fuzzy measure and other different ones, a real data experiment by using a 5-fold cross-validation mean square error (MSE) is conducted. The performances of Choquet integral regression models with fuzzy measure based on extensional L-measure, L-measure, γ- measure, and P-measure, respectively, a ridge regression model, and a multiple linear regression model are compared. Experimental result shows that the Choquet integral regression models with respect to extensional L-measure based on γ-support outperforms others forecasting models. © 2009 IEEE.
Number of references:8
Main heading:Integral equations
Controlled terms: Fuzzy systems - Linear regression - Mean square error
Uncontrolled terms: Choquet integral - Closed form - Cross validation - Forecasting models - Fuzzy measures - L-measure - Multiple linear regression models - Regression model - Ridge regression
Classification code:723.4 Artificial Intelligence - 731.1 Control Systems - 921.2 Calculus - 921.4 Combinatorial Mathematics,
Includes Graph Theory, Set Theory - 922.2 Mathematical Statistics - 961 Systems Science
DOI:10.1109/FSKD.2009.355 Database:Compendex
Compilation and indexing terms, Copyright 2009 Elsevier Inc.
