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土壤含水率与像素颜色之间关系的BP人工神经网络模型
引用本文:李盼盼,缴锡云,马海燕,朱霞.土壤含水率与像素颜色之间关系的BP人工神经网络模型[J].中国农学通报,2008,24(1):463-466.
作者姓名:李盼盼  缴锡云  马海燕  朱霞
作者单位:1. 河海大学水文水资源与水利工程科学国家重点实验室,南京,210098;河海大学农业工程学院,南京,210098
2. 河海大学水文水资源与水利工程科学国家重点实验室,南京,210098
3. 山东水利科学研究院,济南,250013
基金项目:国家科技支撑计划 , 国家重点实验室基金
摘    要:建立像素颜色RGB值与土壤含水率之间的数学关系,是染色入渗法的应用基础。结合沟灌染色入渗试验。研究了染色入渗过程中土壤含水率与像素颜色分量之间关系的BP人工神经网络模型。分析土壤含水率与像素颜色分量之间的关系,确定BP人工神经网络的拓扑结构,以像素颜色分量的相对值作为输入因子。土壤含水率作为输出因子,建立了包含1个隐层的BP人工神经网络。结果表明,该模型具有较高的拟合精度和验证精度,优于二次多项式模型。

关 键 词:染色入渗法  土壤含水率  BP人工神经网络  土壤含水率  像素  颜色分量  数学关系  人工神经  网络模型  Color  Pixel  Soil  Water  Content  Relationship  Neural  Network  Model  多项式模型  拟合精度  验证  结果  隐层  输出因子  输入因子  相对值  拓扑结构
收稿时间:2007-10-23
修稿时间:2007-11-12

BP Artificial Neural Network Model of the Relationship between Soil Water Content and Pixel Color
Li Panpan,Jiao Xiyun,Ma Haiyan,Zhu Xia.BP Artificial Neural Network Model of the Relationship between Soil Water Content and Pixel Color[J].Chinese Agricultural Science Bulletin,2008,24(1):463-466.
Authors:Li Panpan  Jiao Xiyun  Ma Haiyan  Zhu Xia
Abstract:It is necessary to quantify the for the application of dye infiltration. A relationship between pixel color RGB value and soil water content BP artificial neural network model of the relationship between soil water content and pixel color RGB value was researched based on dye infiltration experiment. The topologi- cal structure of a BP Artificial Neural Network was determined based on the relationship between soil water content and pixel color component. Using the relative value of pixel color component as input and soil water content as output, a one - hidden-layer BP Neural Network model was developed. Results show that the proposed model has higher fitting precision and predicting precision, and is superior to quadratic polynomial model.
Keywords:dye infiltration  soil water content  BP artificial neural network
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