Intelligent Fashion Colour Trend Forecasting Schemes: A Comparative Study

Yong Yu, Sau-Fun Ng, Chi-Leung Hui, Na Liu () and Tsan-Ming Choi
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Yong Yu: The Hong Kong Polytechnic University
Sau-Fun Ng: The Hong Kong Polytechnic University
Chi-Leung Hui: The Hong Kong Polytechnic University
Na Liu: The Hong Kong Polytechnic University
Tsan-Ming Choi: The Hong Kong Polytechnic University

Chapter Chapter 8 in Intelligent Fashion Forecasting Systems: Models and Applications, 2014, pp 147-160 from Springer

Abstract: Abstract The colour of a fashion item is one of its key features which often play an important role on the purchase decisions of consumers. And the fashionable colours often prevail in one season, thus, it is crucial for the fashion industry to do forecasting of the fashion trends, especially on colours, prior to the beginning the production for the target season. The lead-time of forecasting becomes shorter recent years with the intensified competition of global fashion industry, and imposes pressure on the forecasting of fashion colour trends. The common practise for the forecasting of colour trends in the fashion industry are based on the ideals of field experts, and the forecasting is in nature fuzzy and hard to be substituted by analytical models. In this paper, we explore the forecasting of colour trends by artificial intelligence models, especially artificial neural network and fuzzy logic models; we observed that such models help to improve the forecasting of fashion colour trends.

Keywords: Artificial Neural Network; Artificial Neural Network Model; Mean Absolute Percentage Error; Fuzzy Neural Network; Fashion Industry (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-3-642-39869-8_8

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