资料稀缺地区径流分析的神经网络模型

Study on Neural Network Model of Annual Runoff in Lack-Data Watershed

资料缺乏和无资料地区的径流分析研究一直是困扰水文工作者的一个难题。在探讨了将人工神经网络方法应用于上述地区的径流研究可行性基础上 ,通过分析确定影响径流的主要因素 ,建立岩溶山区径流分析神经网络模型。

The runoff modeling in the watersheds where there is lack of hydrological data is an important and difficult problem in hydrology. In this paper, based on the neural network theory, an ANN model for runoff, including the recognition composition and structure of the model, is put forward and established. Furthermore, this model was successfully applied the Yunnan MianHua Mountains's runoff analysis. It could be giving a new approach for runoff in lack data watershed and can be applied to solve the other relevant problems.