Optimization Design of Short Life Cycle Product Logistics Supply Chain Scheme Based on Support Vector Machine.

Abstract

In order to better solve the problem of product logistics supply chains with short life cycles, a solution optimization of short life cycle product logistics supply chains based on support vector machines is proposed. This method recommends key technical problems and solutions through information represented by support vector machines and explore the research of short life cycle products to realize logistics supply chains. The research shows that, whether it is a retail channel or a network channel, the RMSE value of the effect index predicted by SVM is smaller than the RMSE value of the improved Bass. It can be seen that the SVM demand forecasting model constructed by considering multiple input factors can obtain a more accurate forecasting effect. The accuracy of the demand forecasting model based on SVM is verified.