Interval-valued dual hesitant fuzzy rough set over two universes and its application

2018 ◽  
Vol 35 (3) ◽  
pp. 3195-3211
Author(s):  
Bingyang Li ◽  
Jianmei Xiao ◽  
Xihuai Wang
Keyword(s):  
Rough Set ◽  
Fuzzy Rough Set ◽  
Two Universes ◽  
Interval Valued

Hesitant fuzzy rough set over two universes and its application in decision making

2015 ◽  
Vol 21 (7) ◽  
pp. 1803-1816 ◽  
Author(s):  
Haidong Zhang ◽  
Lan Shu ◽  
Shilong Liao
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Fuzzy Rough Set ◽  
Two Universes

Dominance-based fuzzy rough set approach for incomplete interval-valued data

2018 ◽  
Vol 34 (1) ◽  
pp. 423-436 ◽  
Author(s):  
Jianhua Dai ◽  
Yuejun Yan ◽  
Zhaowen Li ◽  
Beishui Liao
Keyword(s):  
Rough Set ◽  
Fuzzy Rough Set ◽  
Interval Valued

Probability approach for interval-valued ordered decision systems in dominance-based fuzzy rough set theory

2017 ◽  
Vol 32 (1) ◽  
pp. 703-710 ◽  
Author(s):  
Jianhua Dai ◽  
Guojie Zheng ◽  
Huifeng Han ◽  
Qinghua Hu ◽  
Nenggan Zheng ◽  
...  
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Fuzzy Rough Set ◽  
Decision Systems ◽  
Probability Approach ◽  
Interval Valued

Customer Choice of Super Markets using Fuzzy Rough Set on Two Universal Sets and Radial Basis Function Neural Network

2016 ◽  
Vol 12 (3) ◽  
pp. 20-37 ◽  
Author(s):  
A. Anitha ◽  
Debi Prasanna Acharjya
Keyword(s):  
Neural Network ◽  
Information System ◽  
Radial Basis Function ◽  
Rough Set ◽  
Basis Function ◽  
Real Life ◽  
Customer Choice ◽  
Fuzzy Rough Set ◽  
Radial Basis ◽  
Two Universes

Information and communication technology made shopping more convenient for common man. Additionally, customers compare both online and offline price of a commodity. For this reason, offline shopping markets think of customer satisfaction and try to attract customers by various means. But, prediction of customer's choice in an information system is a major issue today. Much research is carried out in this direction for single universe. But, in many real life applications it is observed that relation is established between two universes. To this end, in this paper the authors propose a model to identify customer choice of super markets using fuzzy rough set on two universal sets and radial basis function neural network. The authors use fuzzy rough set on two universal sets on sample data to arrive at customer choice of super markets. The information system with customer choice is further trained with radial basis function neural network for identification of customer choice of supermarkets when customer size increases. A real life problem is presented to show the sustainability of the proposed model.

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