Computer Science ›› 2016, Vol. 43 ›› Issue (Z11): 455-460.doi: 10.11896/j.issn.1002-137X.2016.11A.102

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Forecasting Method for Fashion Clothing Demand Based on Kernel Functions Technology

MENG Zhi-qing, MA Ke and ZHENG Ying   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Fashion clothing demand forecasting of short life cycle has plagued the production and inventory of garment brand company,and it can not be solved.In this paper,we used the kernel function technique of nonlinear machine lear-ning,and put forward a prediction method for short life cycle fashion clothing.In combination with the characteristics of garment companies and the application of data warehouse,a model of garment demand forecasting based on kernel function was established.We gave a calculation algorithm and carried out the analysis and verification through the actual data.Data experiments show that the proposed method for fashion clothing demand forecasting has higher prediction accuracy,and it is suitable for clothing company dynamic replenishment.It also has important practical significance for the company inventory control.

Key words: Fashion clothing,Demand,Kernel function,Prediction model

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