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A FCM, Grey Model, and BP Neural Network Hybrid Fashion Color Forecasting Method

  • Ran Tao
  • Jie ZhangEmail author
  • Ze-Ping Lv
  • You-Qun Shi
  • Xiang-Yang Feng
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1027)

Abstract

In view of the low prediction accuracy of the existing fashion color prediction methods, this paper propose a fashion color forecasting method used the spring and summer women’s fashion color data released by the International Fashion Color Committee from 2007 to 2013. In preprocess stage, the Pantone color system is used as the color quantization basis, the fuzzy c-means is used to cluster the sample data at first, and a FCM algorithm is used to statistic the color categories in different time series. In forecasting stage, both the grey model and BP neural network are used respectively to construct the fashion color hue prediction model from the statistical results generated from FCM. In evaluation stage, the mean square error is used to compare the prediction effect. The results show that the grey model based on FCM has the smallest error and has the best prediction effect. The proposed model can be used to predict the future fashion color, which can help the apparel industry stakeholders to grasp the trend of the future fashion color and make design and production plan more effectively. The FCM and grey model hybrid prediction method shown in this model also can be used in other small sample data prediction scenario.

Keywords

Clothing fashion color prediction Fuzzy c-means Grey model BP neural network 

References

  1. 1.
    Diane, T., Cassidy, T.: Colour Forecasting, pp. 6–23. Blackwell PublishingLtd., Oxford (2005)Google Scholar
  2. 2.
    Li L.Z.: Color economy and marketing strategy. In: Academic Papers of China Fashion Color Association Academic Annual Conference, pp. 66–71 (2012)Google Scholar
  3. 3.
    Lin, J.J., Sun, P.T., Chen, J.J., et al.: Applying gray model to predicting the trend of textile fashion colors. J. Text. Inst. 101(4), 360–368 (2010)CrossRefGoogle Scholar
  4. 4.
    Liu, G.L., Jiang, Y.: Research on the sensibility of clothing style based on the perceptual cognition of the wearer. J. Text. Res. 11, 101–105 (2007)Google Scholar
  5. 5.
    Chang, L.X. Quantification and prediction of fashion color. Jiangnan University (2013)Google Scholar
  6. 6.
    Di, H.J., Liu, D.Y., Wu, Z.M.: Prediction of popular color in spring and summer women based on bp neural network. J. Text. Res. 32(7), 111–116 (2011). 126Google Scholar
  7. 7.
    Choi, T.M., Hui, C.L., Ng, S.F., et al.: Color trend forecasting of fashionable products with very few historical data. Syst. Man Cybern. 42(6), 1003–1010 (2012)CrossRefGoogle Scholar
  8. 8.
    Zhao, L., Yang, L.H., Huang, X.: Prediction of fashion color of clothing using multi-bee colony cooperative evolution algorithm. J. Text. 39(03), 137–142 (2018)Google Scholar
  9. 9.
    Hu, Z.Q.: Research on the application of trend forecasting of home textile fashion based on grey Markov model and support vector machine. Wuhan Textile University (2018)Google Scholar
  10. 10.
    Chang, L.X., Gao, W.D., Pan, R.R., Liu, J.L.: Application of grey GM(1,1) model in the prediction of popular color hue in international spring and summer women. J. Text. Res. 36(04), 128–133 (2015)Google Scholar
  11. 11.
    Schwarz, M.W., Cowan, W.B., Beatty, J.C.: An experimental comparison of RGB, YIQ, LAB, HSV, and opponent color models. ACM Trans. Graph. 6(2), 123–158 (1987)CrossRefGoogle Scholar
  12. 12.
    Han, W.: Quantitative analysis, prediction, and application of women’s fashion color. Donghua University (2017)Google Scholar
  13. 13.
    Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum, New York (1981)CrossRefGoogle Scholar
  14. 14.
    Deng, J.L.: Control problems of grey systems. Syst. Control Lett. 1(5), 288–294 (1982)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Wang, X.M.: Grey System Analysis and Practical Calculation Program, pp. 50–54. Huazhong University of Science and Technology Press, Hubei (2001)Google Scholar
  16. 16.
    Yang, C.B.: Improved combined forecasting model based on grey model and artificial neural network and its application [Master’s thesis]. Shandong Normal University, Jinan (2009)Google Scholar
  17. 17.
    Chang, L.X., Gao, W.D.: Short-term prediction of international fashion color based on bp neural network. Woolen Technol. 46(02), 87–91 (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ran Tao
    • 1
  • Jie Zhang
    • 1
    Email author
  • Ze-Ping Lv
    • 1
  • You-Qun Shi
    • 1
  • Xiang-Yang Feng
    • 1
  1. 1.School of Computer Science and TechnologyDonghua UniversityShanghaiChina

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