DOI - Mendel University Press

DOI identifiers

DOI: 10.11118/978-80-7701-047-4-0051

ANALYZING CONSUMER BEHAVIOR USING NEURAL NETWORKS AND GRAMMATICAL EVOLUTION

Aleš Ďurčanský1, Kamil Staněk2, Michal Ježek2, Jiří Šťastný1,2
1 Mendel University in Brno, Zemedelska 1665/1, 613 00 Brno, Czech Republic
2 Brno University of Technology, Technicka 2896/2, 619 69 Brno, Czech Republic

In this contribution, we will present an approach to the automatic classification of customers based on their behaviour in the food market. The analysis is based on the data from a survey on meat product consumption in the Czech Republic. Classifiers were created to categorize customers into classes according to their habits of purchasing meat products, dividing the customers with respect to such characteristics as age or education. To accomplish this task some selected types of artificial neural networks (Multi-Layer Perceptron Neural Network, Kohonen Neural Network) were trained and also an approach based on grammatical evolution was used. These classifiers were compared with regard to their abilities to perform the given task. Also, the survey data pre-processing is described.

Keywords: Consumer’s Behaviour, survey analysis, classification, grammatical evolution, neural networks

pages: 51-59, online: 2025



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