DEVELOPMENT OF AN EXPERT SYSTEM FOR CLOTHES STYLE SELECTION BASED ON KANSEI ENGINEERING

Abstract

This research is devoted to implementation of the expert systems for rapid change in production of women's outerwear. Factorial analysis and the cluster analysis are used for the structuring of the subject environment.

Analysis of the emotional component of the garment on the basis of KE can be achieved through cluster analysis. Such an approach will identify models of clothes based on perception and emotional needs of the consumer.

Thus, the main goal of the study was achieved by forming decision-making rules aimed at solving the sub-task of selecting ready-to-wear models based on the Kansei Engineering methodology. The analysis and identification of the formed database of photos of ready-made clothing models was carried out by means of cluster analysis of intergroup relations using the Euclidean distance, which allows for the identification of conditional groups of relatedness of products by design attributes. The obtained final centers of the clusters together with the information about the color solution of the clothing models allowed us to build a product model of an expert system for choosing clothing that meets the formulated wishes of the target consumer.

The object of the study is the women's fashion dresses in spring-summer 2023 season. Thus, a general collection was formed which amounted to 66 photos of fashion dresses for subsequent questionnaire. Work with the software product takes place in the form of a dialogue in the form of consecutive system questions and user answers. The developed system can be used both for the selection of ready-made clothes (for example, in stores, including online stores), and for the selection of a prototype for the development of a new model of clothing that meets the aesthetic needs of the consumers.