Advertisement

Probabilistic Linguistic Linear Least Absolute Regression for Fashion Trend Forecasting

  • Lisheng Jiang
  • Huchang Liao
  • Zhi Li
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 849)

Abstract

Fashion trend is an important aspect in costume designing given that the correct fashion trend prediction can help productions to occupy markets in short time. In the methods of forecast, fuzzy linear least absolute regression is a useful model. Meanwhile, most descriptions about the fashion trend are in nature words which are difficult to be used directly in present models. To deal with this problem, the probabilistic linguistic term set, a powerful tool in expressing and computing nature language, is introduced in this paper. First, operations on probabilistic linguistic term sets are modified to be more logical in the solution procedure of regression. Then a novel model which combines fuzzy linear least absolute regression and probabilistic linguistic term set is developed. Finally, an illustration about the forecast of clothing fashion trend is given to show the applicability of our method in costume designing evaluation.

Keywords

Fashion trend forecasting Fuzzy linear least absolute regression Probabilistic linguistic term set Fuzzy-in and fuzzy-out 

Notes

Acknowledgements

The work was supported by the National Natural Science Foundation of China (71501135, 71771156), and the Scientific Research Foundation for Excellent Young Scholars at Sichuan University (No. 2016SCU04A23).

References

  1. 1.
    Pang, Q., Xu, Z.S., Wang, H.: Probabilistic linguistic term sets in multi-attribute group decision making. Inform. Sciences. 369, 128–143 (2016)CrossRefGoogle Scholar
  2. 2.
    Rodríguez, R.M., Martínez, L., Herrera, F.: Hesitant fuzzy linguistic term sets for decision making. IEEE Trans. Fuzzy Syst. 20(1), 109–119 (2012)CrossRefGoogle Scholar
  3. 3.
    Liao, H.C., Xu, Z.S., Herrera-Viedma, E., Herrera, F.: Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the-art survey. Int. J. Fuzzy Syst. (2017).  https://doi.org/10.1007/s40815-017-0432-9CrossRefGoogle Scholar
  4. 4.
    Liao, H.C., Jiang, L.S., Xu, Z.S., Xu, J.P., Herrera, F.: A probabilistic linguistic linear programming method in hesitant qualitative multiple criteria decision making. Inform. Sciences. 415–416, 341–355 (2017)CrossRefGoogle Scholar
  5. 5.
    Zhang, Y.X., Xu, Z.S., Wang, H., Liao, H.C.: Consistency-based risk assessment with probabilistic linguistic preference relation. Appl. Soft Comput. 49, 817–833 (2016)CrossRefGoogle Scholar
  6. 6.
    Tanaka, H., Uejima, S., Asai, K.: Linear regression analysis with fuzzy model. IEEE Trans. Syst. Man Cybern. 12, 903–907 (1982)CrossRefGoogle Scholar
  7. 7.
    Pourahmad, S., Ayatollahi, S.M.T., Taheri, S.M., Agahi, Z.H.: Fuzzy logistic regression based on the least squares approach with application in clinical studies. Comput. Math Appl. 62, 3353–3365 (2011)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Zeng, W.Y., Feng, Q.L., Li, J.H.: Fuzzy least absolute linear regression. Appl. Soft Comput. 52, 1009–1019 (2017)CrossRefGoogle Scholar
  9. 9.
    Charnes, A., Cooper, W.W., Ferguson, R.: Optional estimation of executive compensation by linear programming. Manage. Sci. 2, 138–151 (1995)Google Scholar
  10. 10.
    Zadeh, L.: A note on Z-numbers. Inform. Sci. 181, 2923–2932 (2011)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Jiang, S.Y.: Analysis of the importance of fashion trends in clothing design. West. Leather. 67 (2017)Google Scholar
  12. 12.
    Han, J.Y.: A preliminary study on fashion trend prediction. The new World Forecast. 4, 56–58 (1991)Google Scholar
  13. 13.
    Mello, P., Storari, S., Valli, B.: Application of machine learning techniques for the forecasting of fashion trends. Intelligenza Artificiale. (2008)Google Scholar
  14. 14.
    Jia, S., Zhu, S.G., Victor, K.: Based on the transformation and upgrading of garment industry in PingHu, a new prediction method of fashion trend is analyzed: an example of female dress profile analysis. Spec. Topic Discuss. 5, 81–88 (2016)Google Scholar
  15. 15.
    Liao, H.C., Jiang, L.S., Benjamin L.: Probabilistic linguistic ELECTRE III based on new operations. IEEE Trans. Fuzzy Syst. Technique ReportGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Business SchoolSichuan UniversityChengduChina

Personalised recommendations