摘要
利用带动量项学习规则的改进 BP算法 ,对三江平原创业农场井灌水稻区逐月地下水埋深进行了模似仿真 ,将人工神经网络技术 (ANN)与广大井灌水稻区生产实际相结合 ,通过网络检验与预测 ,模型精度与预测精度均达到满意效果。该网络模型对于节约地下水开采量 ,恢复该地区的地下水动态平衡、制定农作物优化灌溉制度、发展节水灌溉。
Through applying a kind of mended BP arithmetic,which has momentum learning regular,the paper simulate the monthly groundwater depth about well irrigation rice of Chuang Ye Farm in San Jiang Plain.Combining the artificial neural networks with the practical problem of the area of well irrigation rice,the writer buids up the ANN model.Through testing and forecasting,the model precision and forecasting precision are high.So,the ANN model can provide some references for many aspects,such as saving groundwater resources,resuming the balance of groundwater in this area,establishing the optimum irrigation system of well irrigation rice,developing water saving irrigation and so on.It can advance the agriculture and water resource to develop continuum also.$$$$
出处
《东北农业大学学报》
CAS
CSCD
2002年第2期152-159,共8页
Journal of Northeast Agricultural University
关键词
人工神经网络
井灌水稻区
地下水位预测
BP算法
井灌水稻
Artificial Neural Networks(ANN),Back-Propagation Arithmetic (BP),well irrigation rice,groundwater
