BP神经网络在农机总动力预测中的应用  

Application of BP Neural Network in Total Power of Agriculture Machinery Forecast

作　　者：王吉权[1] 邱立春[2] 王福林[1] 王英[1] 任艳杰[1] 孙福田[1] 

机构地区：[1]东北农业大学工程学院,黑龙江哈尔滨150030 [2]沈阳农业大学工程学院,辽宁沈阳11016

出　　处：《数学的实践与认识》2013年第1期72-79,共8页Mathematics in Practice and Theory

基　　金：黑龙江省教育厅项目(12511049);辽宁省自然科学基金项目(20052127);黑龙江省科技攻关项目(NB08B-011)

摘　　要：准确的预测黑龙江省农机总动力,可为黑龙江省的农业机械化发展趋势和农机产品市场分析提供理论指导,为制定黑龙江省农业机械化发展规划和预测近阶段农业机械化发展水平提供参考依据.利用黑龙江省1980-2007年农机总动力数据,运用标准BP神经网络和改进BP神经网络模型进行预测,预测结果表明,改进BP神经网络模型比标准BP神经网络模型在预测精度、运行时间、学习次数等方面更具优越性.To accurately predict the total power of agriculture machinery for Heilongjiang Province, which can provide theoretical guidance for the development trends of agricultural mechanization and for the market analysis of agricultural product in Heilongjiang Province, can provide references for the development planning of agricultural mechanization and the forecasting the development level of agricultural mechanization in recent stage in Heilongjiang Province. In this paper, we applied the data of total power of agriculture machinery in Heilongjiang Province from 1980 to 2007, using the standard BP neural network and the improved BP neural network model to predict, the forecasting results showed that the improved BP neural network model had more advantages than the standard BP neural network model in forecasting accuracy, running time and learning frequence.

关 键 词：标准BP神经网络 改进BP神经网络 农机总动力 预测 

分 类 号：S210.6[农业科学—农业机械化工程] TP183[农业科学—农业工程]