Introduction to Grey system theory
The Journal of Grey System
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Form design of product image using grey relational analysis and neural network models
Computers and Operations Research
A fashion mix-and-match expert system for fashion retailers using fuzzy screening approach
Expert Systems with Applications: An International Journal
Evolving neural network using real coded genetic algorithm for daily rainfall-runoff forecasting
Expert Systems with Applications: An International Journal
Artificial intelligence diagnosis algorithm for expanding a precision expert forecasting system
Expert Systems with Applications: An International Journal
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Forecasting stock exchange movements using neural networks: Empirical evidence from Kuwait
Expert Systems with Applications: An International Journal
A two-stage dynamic sales forecasting model for the fashion retail
Expert Systems with Applications: An International Journal
A hybrid SARIMA wavelet transform method for sales forecasting
Decision Support Systems
A Neuro-Fuzzy Inference System Through Integration of Fuzzy Logic and Extreme Learning Machines
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A New and Efficient Intelligent Collaboration Scheme for Fashion Design
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Forecasting future color trend is a crucially important and challenging task in the fashion industry including design, production and sales. In particular, the trend of fashion color is highly volatile. Without advanced methods, it is very hard to make fashion color trend forecasting with reasonably high accuracy, and it is a handicap for development of the intelligent expert systems in fashion industry. As a result, many prior works have employed traditional regression models like ARIMA or intelligent models such as artificial neural network (ANN) and grey model (GM) for conducting color trend forecasting. However, the reported accuracies of these forecasting methods vary a lot, and there are controversies in the literature on these models' performances. As a result, in this paper, we systematically compare the performances of ARIMA, ANN and GM models and their extended family methods. With real data analysis, our results show that the ANN family models, especially for Extreme Learning Machine (ELM) with Grey Relational Analysis (GRA), outperform the other models for forecasting fashion color trend.