基于核函数技术的时尚服装需求预测方法

短生命周期的服装需求预测问题一直是服装品牌公司无法解决的问题,运用了非线性机器学习的核函数技术,提出了一个适合短生命周期时尚类服装的预测方法。结合服装公司的产品特征和服装数据仓库应用研究,建立了一种基于核函数技术的服装需求预测模型,提出了一个计算算法,通过实际数据进行了分析验证,结果表明所提出的方法对于时尚服装需求预测具有较高的动态预测精度,适合服装公司进行动态补货,对于品牌公司控制库存具有重要的实际意义。

Forecasting Method for Fashion Clothing Demand Based on Kernel Functions Technology

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.