摘要
针对农资物流需求预测指标体系,结合粗糙集(RS)和支持向量机(SVM)方法的优点,建立了基于RS-SVM的农资物流需求预测模型,设计并实现了农资物流需求预测子系统,为农资物流需求预测提供了有效方法,为企业提供了有力的决策支持。
The thesis for the agricultural materials logistics demand forecasting index system combines the method of Rough sets （RS） and Support vector machine （SVM） to set up the agricultural materials demand forecasting model based on RS- SVM, then it is designed and implemented the function of the agricultural materials logistics demand forecasting subsystem. It is provided the effective method for the agricultural materials logistics demand forecasting and it is provided the strong decision support for the enterprise.
出处
《湖北农业科学》
2015年第8期1985-1987,共3页
Hubei Agricultural Sciences
基金
河北省自然科学基金项目(G2014402027)
河北省科技支撑计划项目(12213522D
13227111D)
关键词
物流配送
农资需求
预测
粗糙集
支持向量机
logistics distribution
agricultural demand
forecasting
rough sets
support vector machine
