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

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

A. Anitha, Debi Prasanna Acharjya
Copyright: © 2016 |Volume: 12 |Issue: 3 |Pages: 18
ISSN: 1548-3657|EISSN: 1548-3665|EISBN13: 9781466689428|DOI: 10.4018/IJIIT.2016070102
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MLA

Anitha, A., and Debi Prasanna Acharjya. "Customer Choice of Super Markets using Fuzzy Rough Set on Two Universal Sets and Radial Basis Function Neural Network." IJIIT vol.12, no.3 2016: pp.20-37. http://doi.org/10.4018/IJIIT.2016070102

APA

Anitha, A. & Acharjya, D. P. (2016). Customer Choice of Super Markets using Fuzzy Rough Set on Two Universal Sets and Radial Basis Function Neural Network. International Journal of Intelligent Information Technologies (IJIIT), 12(3), 20-37. http://doi.org/10.4018/IJIIT.2016070102

Chicago

Anitha, A., and Debi Prasanna Acharjya. "Customer Choice of Super Markets using Fuzzy Rough Set on Two Universal Sets and Radial Basis Function Neural Network," International Journal of Intelligent Information Technologies (IJIIT) 12, no.3: 20-37. http://doi.org/10.4018/IJIIT.2016070102

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Abstract

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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