摘要： 为正确估算产品间的替代率，提高需求预测准确率，提出一种基于加权欧式距离的邻近替代率估计方法，建立基于支持向量机的需求预测模型。在洗面奶数据集中的应用结果表明，该方法预测精度较高，具有客观性和有效性。

关键词: 邻近替代, 加权欧式距离, 复相关系数, 支持向量机, 需求预测

Abstract: In this paper, an adjacent substitution rate estimation method based on weighted Euclid distance is proposed in order to improve the disadvantage of estimating weight by experience. It is based on Support Vector Machine(SVM). The proposed method is applied to the demand forecast of facial cleaning category. Experimental results identify that the predict precision is improved and the objectivity and robustness are both well.

Key words: adjacent substitution, weighted Euclid distance, compound correlation coefficient, Support Vector Machine(SVM), demand forecast

中图分类号: 

• TP311.5