摘要
根据福建省过去十几年航空货物发送量的数据,针对航空物流预测的不确定性,将粒子群优化算法和最小二乘支持向量机相结合,采用粒子群优化最小二乘支持向量机的方法来建立模型。并将优化后的最小二乘支持向量机模型应用于福建省航空物流的需求预测中,而后通过仿真对结果进行验证。
According to the data of air freight volume throughout of Fujian in the past decades,considering the uncertainty of the forecast in the aviation logistics demand. A model which use the particle swarm algorithm to optimize the LS- SVM is established,and then applied to predict the aviation logistics demand of Fujian. Finally the results are verified by simulation.
出处
《物流工程与管理》
2014年第7期52-54,共3页
Logistics Engineering and Management
