Abstract
In this study, a GM(1,1) model is applied to forecast the trend of textile fashion colors. Through the historical time series data of the color suggestion ratios by international forecasting facilities in the past, the GM(1,1) model is applied to forecast the fashion color trend. Besides the GM(1,1) model, a gray neural network model (i.e. GNNM(1,1)) is developed to compare the precision with it as well. The simulated results show that the GM(1,1) model has higher forecast precision than the GNNM(1,1) one. The predicted results of the color trend using the GNNM(1,1) model are less close to the real circumstances than as expected. With the assistance of a gray model-based prediction model, the fashion color trend can be traced more precisely and easily.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
