A Choquet integral regression model with a new fuzzy measure based on multiple mutual-information

Author(s):  
Hsiang-Chuan Liu ◽  
Horng-Jinh Chang ◽  
Wen-Chih Lin ◽  
Kai-Yi Chang
2020 ◽  
Vol 54 (2) ◽  
pp. 597-614
Author(s):  
Shanoli Samui Pal ◽  
Samarjit Kar

In this paper, fuzzified Choquet integral and fuzzy-valued integrand with respect to separate measures like fuzzy measure, signed fuzzy measure and intuitionistic fuzzy measure are used to develop regression model for forecasting. Fuzzified Choquet integral is used to build a regression model for forecasting time series with multiple attributes as predictor attributes. Linear regression based forecasting models are suffering from low accuracy and unable to approximate the non-linearity in time series. Whereas Choquet integral can be used as a general non-linear regression model with respect to non classical measures. In the Choquet integral based regression model parameters are optimized by using a real coded genetic algorithm (GA). In these forecasting models, fuzzified integrands denote the participation of an individual attribute or a group of attributes to predict the current situation. Here, more generalized Choquet integral, i.e., fuzzified Choquet integral is used in case of non-linear time series forecasting models. Three different real stock exchange data are used to predict the time series forecasting model. It is observed that the accuracy of prediction models highly depends on the non-linearity of the time series.


2007 ◽  
pp. 1349-1355 ◽  
Author(s):  
HSIANG-CHUAN LIU ◽  
WEN-CHIH LIN ◽  
WEI-SHENG WENG

2016 ◽  
pp. 825-829
Author(s):  
Hsiang-Chuan Liu ◽  
Hsien-Chang Tsai ◽  
Yen-Kuei Yu ◽  
Yi-Ting Mai

2010 ◽  
Vol 44-47 ◽  
pp. 3844-3848
Author(s):  
Shu Juan Lee ◽  
Hsiang Chuan Liu ◽  
Shih Ming Chen ◽  
Yu Du Jheng

In this study, the Web-based Multi-Survey System was adopted, one or two choices available among five options, to set up questionnaire to get a nine-point scale with network programs. As an empirical research, which was conformed to the policy of Ministry of Education to promote technology abilities for teachers in Taichung County in 2009, the important and satisfied survey from Teachers’ Free Software Application workshops was analyzed by four approaches which were Importance-Performance Analysis, Simple Logistic regression model, Choquet integral regression model with respect to λ-measure, and Choquet integral regression model with respect to L-measure. By comparing MSE, Choquet integral regression model with L-measure obtained the best performance. Two crosshairs which were Hollenhorst’s overall mean and Choquet integral regression model with L-measure were positioned for I-P matrix. From results, the L-measure model had shown better sensitivity about quadrant distribution, and reflected participants’ real responses. At the same time, it was definitely known what to keep up the good work, concentrate here, or possible overkill through assessing Importance and Performance of teacher’s workshops.


Author(s):  
T. MUROFUSHI ◽  
M. SUGENO

This paper discusses multiattribute preference relations compatible with a value/utility function represented by the Choquet integral with respect to a fuzzy measure, and shows that the additivity of the fuzzy measure is equivalent to each of mutual preferential independence, mutual weak difference independence, mutual difference independence, mutual utility independence, and additive independence.


2014 ◽  
Vol 602-605 ◽  
pp. 3379-3383
Author(s):  
Yong Sheng Liu ◽  
Zan Zhang

In multiattribute decision making, it is critical to indentify the importance degree of attributes before the overall assessment of the alternatives. In this paper, we give a measurement of importance degree of attributes based on knowledge discovery in the decision information system, which satisfies the conditions of fuzzy measure. Further, we construct an evaluation model combined Choquet integral with the importance degree measure. The case study illustrates the validity and the effectiveness of the method.


2018 ◽  
Vol 292 ◽  
pp. 151-164 ◽  
Author(s):  
Andre G.C. Pacheco ◽  
Renato A. Krohling

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