Learning‐based fuzzy colour prediction system for more effective apparel design

Abstract

Purpose -This paper aims to design and develop a learning-based fuzzy colour prediction system for providing more effective apparel design in computer-aided design system. Design/methodology/approach -In this study, we propose using a fuzzy system integrated with preliminary knowledge of colour prediction for facilitating apparel design. The performance of the proposed system is evaluated in terms of its computational efficiency and robustness. In addition, the proposed system is evaluated by target group of customers. Findings -It was found that the performance of the proposed system is better than the traditional approach.Research limitations/implications -Although the proposed system has some limitations, the outcome of this study could be used to produce a future breakthrough in providing an intelligent computer-aided design system for apparel product. Originality/value -Using such an approach, an apparel designer could predict the favourite colours of garment for a target group of customers. The system uses preliminary knowledge about the customers' profiles and evaluations. Such fuzzy approach for colour prediction is established, which is not used in a traditional way in apparel design.

Sales Forecasting for Fashion Retailing Service Industry: A Review

“…In addition, the multivariate fuzzy logic model performs better in comparison to the univariate counterparts. Later on, Hui et al [28] explore the demand prediction problem in terms of fashion color forecasting. They propose a fuzzy logic system which integrates preliminary knowledge of colour prediction with the learning-based fuzzy colour prediction system to conduct forecasting.…”

Applications of artificial intelligence in the apparel industry: a review

“…Hui et al 24 developed a learning-based fuzzy system to predict the favorite colors of garments for a target group of customers based on customers’ profiles, such as gender, age, height, and skin color. However, this system is only applicable to single-color prediction cases.…”

“…Chen et al 29,30 utilized fuzzy systems to generate the fuzzy ease allowance at each key body position. To establish the relationship between customers’ profiles and their favorite colors, Hui et al 24 developed a fuzzy system that used preliminary knowledge about the customers’ profiles and color evaluations to generate fuzzy rules. Wang et al 35 presented a fuzzy system to predict the subjective perceptions of thermal comfort.…”

“…Most of them focused on the applications of AI to specific decision-making problems in the apparel industry. 11–14,16–24 However, little research investigated their significance to the theoretical development of these research subjects, which hinders the extension of these research outputs in the apparel industry to other industries and makes relatively few contributions to their theoretical developments.…”

Item-level RFID for enhancement of customer shopping experience in apparel retail

“…Because of the ability to handle imprecise or vague information like human reasoning, FL has been successfully applied in apparel retail for decision support and evaluation on apparel collocation [13] [14]. In [15], the literature line of FL in decision-making has been extended from single-criterion to multiple-criteria, which are more feasible and versatile in the apparel industry.…”