ANALYZING CONSUMER BEHAVIOR USING NEURAL NETWORKS AND GRAMMATICAL EVOLUTION
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F26%3A0198812" target="_blank" >RIV/00216305:26210/26:0198812 - isvavai.cz</a>
Nalezeny alternativní kódy
RIV/62156489:43110/25:43927610
Výsledek na webu
<a href="https://doi.mendelu.cz/pdfs/doi/9900/10/1400.pdf" target="_blank" >https://doi.mendelu.cz/pdfs/doi/9900/10/1400.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.11118/978-80-7701-047-4-0051" target="_blank" >10.11118/978-80-7701-047-4-0051</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
ANALYZING CONSUMER BEHAVIOR USING NEURAL NETWORKS AND GRAMMATICAL EVOLUTION
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
ANALYZING CONSUMER BEHAVIOR USING NEURAL NETWORKS AND GRAMMATICAL EVOLUTION
Popis výsledku anglicky
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.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/EF16_017%2F0002334" target="_blank" >EF16_017/0002334: Výzkumná infrastruktura pro mladé vědce</a><br>
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
ECONOMIC COMPETITIVENESS AND SUSTAINABILITY 2025
ISBN
978-80-7701-047-4
ISSN
—
e-ISSN
—
Počet stran výsledku
9
Strana od-do
51-59
Název nakladatele
—
Místo vydání
—
Místo konání akce
Mendel University in Brno, Czech Republic
Datum konání akce
27. 3. 2025
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—