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支持向量机在弹药训练消耗量预测中的应用
引用本文:宋彬,龚传信,管维荣.支持向量机在弹药训练消耗量预测中的应用[J].军械工程学院学报,2006,18(1):43-45.
作者姓名:宋彬  龚传信  管维荣
作者单位:军械工程学院装备指挥与管理系 河北石家庄050003
摘    要:针对部队平时弹药训练消耗量预测过程中,样本采集数目较少的实际情况,采用了一种新的预测方法———支持向量机。该方法基于统计学习理论的原理,较好地解决了小样本的学习问题。并以某部队1997—2002年弹药训练消耗量为学习样本,建立了弹药年消耗量的预测模型。计算结果表明,这种方法比传统的方法有更少的误差和更好的预测精度。

关 键 词:支持向量机  弹药消耗量  预测  样本
文章编号:1008-2956(2006)01-0043-03
修稿时间:2005年8月30日

Supporting Vector Machine on Ammunition Consumption Level Prediction in Training
SONG Bin,GONG Chuan-xin,GUAN Wei-rong.Supporting Vector Machine on Ammunition Consumption Level Prediction in Training[J].Journal of Ordnance Engineering College,2006,18(1):43-45.
Authors:SONG Bin  GONG Chuan-xin  GUAN Wei-rong
Abstract:Based on the situation that the number of test samples is few in the course of predicting annual ammunition consumption level in training,a new method,support vector machine is given.The algorithm is based on statistical theory.It can better solve learning problem of small sample.By using the historical statistical data of ammunition consumption level from 1997 to 2002 as learning sample,a model is built to predict ammunition consumption level.The results show that the method can bring less error and better predicted precision compared with the traditional methods.
Keywords:support vector machine  ammunition consumption level  predict  sample
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