New fuzzy BP neural network and its application in the network management;

The segment fuzzy BP Neural Network is adopted to predict the passenger traffic volume of railways in data mining based on analyzing the data feature of railway passenger tickets.

Then, the formulas of difference functions and relative membership degree, model of BP neural network with fuzzy optimization, equation of rank feature values are presented, and relevant equations are analyzed.

Diagnosis concrete process of the method is as follows: wavelet packet decomposition is adopted to extract Shannon entropy of sample signals from each frequency band,and which combining with other quantitative index served as eigenvector to input rolling bearing fault diagnosis based on high-order fuzzy neural network after be selected.

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.