火力与指挥控制2011，Vol.36Issue(6)：171-175,5.
基于PSO-SVM与样本加权的武器装备费用建模与预测
The Modeling and Forecasting of Weapon Equipment Expenses Based on PSO-SVM and Sample Weighting
袁冬根 1刘晓东 1王晓明 1蔡磊1
作者信息
- 1. 空军工程大学工程学院，西安,710038
- 折叠
摘要
Abstract
Forecasting of weapon equipment expenses is the important content in expenses analysis of weapon equipment. One of the difficulties in forecasting and analyzing is the shortage and complicated nonlinear characteristics of sample data. This paper makes better use of the characteristics which is owed by the structure risk minimization of support vector machine and fast overall optimizing of particle swarm. The particle swarm optimization is used to optimize the parameters of the support vector machine. The sample weighting value in the model adopts the methods of estimate error and similarity of sample to make better use of the sample information. The prediction Model for Weapon equipment expenses based on PSO-SVM and sample weighting is established and improves the effect of model prediction. Finally, the feasibility of that method is proved with the example. The model provides a new thought for the research of weapon equipment expenses forecasting.关键词
费用预测；粒子群算法；支持向量机；样本加权Key words
expenses forecasting, particle swarm optimization, support vector machine, sample weighting分类
信息技术与安全科学引用本文复制引用
袁冬根,刘晓东,王晓明,蔡磊..基于PSO-SVM与样本加权的武器装备费用建模与预测[J].火力与指挥控制,2011,36(6):171-175,5.
