基于灰色关联分析与BP神经网络模型的　日参考作物蒸发蒸腾量预测  

Forecast of Daily Reference Evapotranspiration Based on Gray Relation Analysis and BP Neural Network

作　　者：马亮[1] 何继武[2] 

机构地区：[1]新疆农业大学水利与土木工程学院,新疆乌鲁木齐830052 [2]新疆农业大学新疆农业大学科研管理处,新疆乌鲁木齐830052

出　　处：《水资源与水工程学报》2009年第6期34-37,共4页Journal of Water Resources and Water Engineering

基　　金：国家863计划(2006AA100218);国家科技支撑计划(2007BAD38B01);新疆维吾尔自治区重大科技专项(20073117-1);新疆水利水电工程重点学科基金(XJZDXK2002-10-05)

摘　　要：采用灰色系统理论中的关联分析方法,对影响作物蒸发蒸腾量的各个气象因素进行关联度分析,挑选出影响作物蒸发蒸腾量的主要气象因子,并以这些气象因子为输入向量,以参考作物蒸发蒸腾量为输出向量,建立作物蒸发蒸腾量与主要气象因子之间的BP神经网络预测模型。实例证明:该方法简单可行,预测精度较高,能满足实际生产需要。Using the interaction analytical method in gray system theory,this paper analyzed all the factors which affected crop evapotranspiration and selected out the main climatic factors.The input vectors were various climatic factors,while the output was the daily reference evapotranspiration,the BP neural network forecast model was established.By means of experiment,this method is easy, accurate and convenient for practical application.

关 键 词：参考作物蒸发蒸腾量 灰色关联度 BP神经网络 

分 类 号：S161.4[农业科学—农业气象学]