ANALYZING CONSUMER BEHAVIOR USING NEURAL NETWORKS AND GRAMMATICAL EVOLUTION

článek ve sborníku ve WoS nebo Scopus

en

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.

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.

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

27.03.2025

978-80-7701-047-4

ECONOMIC COMPETITIVENESS AND SUSTAINABILITY 2025

51–59

9