农机化研究2017，Vol.39Issue(7)：34-38,5.
新疆兵团农机总动力预测模型的研究
Research on the Prediction Model of Agricultural Machinery Total Power in Xinjiang Corps
摘要
Abstract
In order to improve the precision of forecast model of agricultural machinery total power in Xinjiang corps and obtain more reliable predictions , focus on the problems of regression model of multicollinearity and grey model containing only exponential growth trend ,based on the data of 2007 to 2014 related to agricultural power ,established principal com-ponent regression and gray regression model .The prediction accuracy of the two models were compared , and the results showed that the average relative error of predicted values of the principal component regression model and grey regression model were 0 .57% and 0 .46%.The gray regression prediction model is of high precision and can truly reflect the change of agriculture machinery total power of Xinjiang corps .The model is applied to forecast and obtained the forecast value of agricultural machinery total power of xinjiang corps in the next five years .关键词
农机总动力/预测模型/主成分回归模型/灰色回归模型Key words
total power of agricultural machinery/forecast model/principal component regression model/gray regres-sion model分类
农业科技引用本文复制引用
刘银萍,陈永成,曹卫彬,毕新胜..新疆兵团农机总动力预测模型的研究[J].农机化研究,2017,39(7):34-38,5.基金项目
国家自然科学基金项目 （）
