Estimating nitrogen content of corn based on wavelet energy coefficient and BP neural network

摘要：

In order to estimate the nitrogen content of corn in natural environment timely and accurately,we developed a method to determine the nitrogen status of corn based on wavelet energy coefficient and BP neural network.Hyperspectral reflectance (350-1300nm) was performed by wavelet transform using Daubechies 5 wavelet function and nine level wavelet coefficients of spectral reflectance. Wavelet energy coefficients and nitrogen content were used as the independent and dependent variable of regression model,respectively.Of all the models,wavelet energy coefficient F2 as the independent variable achived the best with R2 of 0.905.A BP neural network model based on a five wavelet energy coefficients (F1-F5) with relative R2was used as input parameters,and output parameter of the output layer was nitrogen content.The result showed that an optimum BP neuralnetwork prediction model has 5-4-1 network architecture with R2 of 0.932 and root mean square error (RMSE) of 0.097.The result indicates that the model with wavelet energy coefficient and BP neural network can extract characteristic variables from hyperspectra.Compared with the regression analysing model,it can improve the accuracy of estimation of corns nitrogen content.

关键词： hyperspectral nitrogen content wavelet analysing BP neural network wavelet energy coefficient

作者: Lina Xiu Xiangnan Liu Hui Zhang

作者单位: Department of Management Engineering.Tianjin Institute of Urban Construction,Tianjin,China School o School of Information Engineering,China University of Geosciences,Beijing,China Department of Electronic and Information Engineering,Tianjin Institute of Urban Construction,Tianjin

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 144-147

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）