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基于偏最小二乘回归的装备备件消耗预测
引用本文:刘浏,罗广旭,魏东涛,刘妍,赵徐成,王保成.基于偏最小二乘回归的装备备件消耗预测[J].数学的实践与认识,2017(10):122-126.
作者姓名:刘浏  罗广旭  魏东涛  刘妍  赵徐成  王保成
作者单位:1. 空军勤务学院航空四站系,江苏徐州,221000;2. 空军勤务学院基础部,江苏徐州,221000
摘    要:考虑了装备使用时间、行驶里程和配备时间等影响备件消耗的多种因素,依据装备备件的消耗特点,在分析偏最小二乘回归方法原理的基础上,运用方法对小样本数据条件下装备备件的消耗数量进行预测.应用示例表明,偏最小二乘回归方法比传统多元回归分析法、逐步多元回归分析法和删除多元回归分析法具有更高的预测精度.

关 键 词:偏最小二乘回归  小样本  备件消耗

Spare Parts Consumption Prediction Based on Partial Least-Squares Regression
LIU Liu,LUO Guang-xu,WEI Dong-tao,LIU Yan,ZHAO Xu-cheng,WANG Bao-cheng.Spare Parts Consumption Prediction Based on Partial Least-Squares Regression[J].Mathematics in Practice and Theory,2017(10):122-126.
Authors:LIU Liu  LUO Guang-xu  WEI Dong-tao  LIU Yan  ZHAO Xu-cheng  WANG Bao-cheng
Abstract:Through making a analysis of the factors which include operation time,actual service life and the age of the equipment and the character of spare parts consumption,the partial least-squares regression is applied to solve the problem of spare parts consumption prediction when the sample is small.The example indicates that partial least-squares regression is much more accurate than traditional multiple linear regression,stepwise multiple linear regression and erasing multiple linear regression.
Keywords:partial least-squares regression  small sample  spare parts consumption
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