An expert system for perfume selection using artificial neural network

Authors:
Payam Hanafizadeh;Ahad Zare Ravasan;Hesam Ramazanpour Khaki
Affiliations:
Department of Management and Accounting, Allemeh Tabataba'i University of Tehran, Iran;Department of Management and Accounting, Allemeh Tabataba'i University of Tehran, Iran;Department of Management and Accounting, Allemeh Tabataba'i University of Tehran, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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Abstract

The objective of this research is to help customers in purchasing perfumes, with the aid of the expert system program developed by using artificial neural networks. The expert system's role is in the preparation to capture the data from the customer's requirements and predict appropriate perfume. For this end, factors of perfume costumers' decision were recognized using Fuzzy Delphi method and a back propagation neural network classification model was developed and trained with 2303 data of customers. In addition, to validate the approach, the expert system program has been tested with 583 data of customers. The model demonstrates the usefulness of 70.33% classification rate in classifying consumers' styles that looks satisfying.