In order to consider the factors synthetically on safety evaluation, the BP network model is adopted to build up the safety evaluation method of dykes and dams by the artificial neural network.

Based on existing theories and actual values from current standards,the effects of major factors affecting ACSR are quantified,and based on BP network model,the coefficient is estimated using C code.

the cluster′s index is chosen based on the valid precipitation in each growth period and the sensitiveness coefficient,and fuzzy clustering iteration model is utilized to cluster the data of many years precipitation of irrigation section,then the BP network model is formed,finally,the change tendency of the profit and loss of agricultural moisture in the future is forecasted.

The Study on the Forecasting Methods of Urbanization level——Taking BP Neural Network Model as an Example;

Through the establishment of water environment management information system of Supa River basin, an improved BP neural network model made for the comprehensive assessment on the water quality of the basin concerned is presented in accordance with the condition with better water quality and without any principal economic industries therein.

It is introduced that the BP neural network model of prediction of mining collapse is established based on the survey′s data and main factors at a mine field where the collapse had happen.

Then the wavelet network model is established by the combination of BP neural network and used to forecast annual runoff at Beipei hydrologic station,and the forecasted result is compared with the forecasted result by BP neural network.

The principal component analysis of factors of BP neural network model and statistical regression model has been carried out by an example; and the effects of factor correlativity on the two kinds of dam monitoring models are studied.

BP neural network of LM calculation method was designed with Matlab language for predicting the road traffic noise.