Application of BP neural network model with fuzzy optimization in retrieval of biomass parameters  

模糊优选神经网络BP模型在植被生物量参数反演中的应用(英文)

作　　者：陈守煜[1] 郭瑜[1] 

机构地区：[1]大连理工大学土木水利学院水资源教研室,大连116024

出　　处：《Agricultural Science & Technology》2005年第2期7-11,共5页农业科学与技术（英文版）

基　　金：国家自然科学基金资助项目(59149002,59179376);高等学校博士学科点专项科研基金资助项目(9014102)

摘　　要：The retrieval of the biomass parameters from active/passive microwave remote sensing data （10.2 GHz） is performed based on an iterative inversion of BP neural network model with fuzzy optimization. The BP neural network is trained by a set of the measurements of active and passive remote sensing and the ground truth data versus Day of Year during growth. Once the network training is complete, the model can be used to retrieve the temporal variations of the biomass parameters from another set of observation data. The model was used in weights and microware observation data of wheat growth in 1989 to retrieve biomass parameters change of wheat growth this year. The retrieved biomass parameters correspond well with the real data of the growth, which shows that the BP model is scientific and sound.根据模糊优选神经网络BP模型,利用1988年小麦生长期中生物量参数和微波(10.2GHz)主被动遥感实测数据,作为输入输出I/O矢量对,计算出网络模型的正向传输权重矩阵及反向传输权重矩阵。用1989年小麦生长期中微波实测数据和该神经网络模型得到的权重矩阵,来反演其生物量参数在整个1989年生长期中的变化,反演结果与遥感实测结果的比较说明了所提方法的准确性。

关 键 词：ANN BP model biomass parameters RETRIEVAL 

分 类 号：Q94-3[生物学—植物学]