This paper establishes the nonlinear relationship predication model of artificial neural network (ANN) between the drinking water chemistry indicators and the morbidity of Kaschin-Beck disease in Sichuan districts by BP (Back-Propagation) arithmetic Firstly, the input for the network are determined by the result of correlation analyses which analyses the water chemistry indicators and the morbidity of Kaschin-Beck disease, the output for the network is determined by the morbidity of Kaschin-Beck disease which have been obtained through to Zamtang county in Sichuan Province on-the-spot investigation Then the hidden units for the network using the trial-and-error method, finally, the writer builds an ANN model for the simulation and prediction of water quality in Sichuan Kaschin-Beck disease districts, the structure of which model is 9∶10∶1 At last, the Model of artificial neural network calculates using the MATLAB It achieved the high simulation precision and the desired results of training, then carries on the confirmation with the establishment model to the new sample, and it has obtained the high forecast precision The results show that the model can establish the good relationship between Kaschin-Beck disease and the drinking water The analyses made with this model show that the precision of both the simulation and prediction is high, so this model can be applied to forecast the morbidity of Kaschin-Beck disease The model has great applied and popularized value

ANN approach for modeling and prediction of water quality in Sichuan Kaschin-Beck disease districts

Artificial Neural Network(ANN) is an effective method of data analysis and way of processing, which is widely used. In the article BP artificial neural network was used to set up groundwater quality assessment model in Industrial Park Catchment. The matlab toolbox was used to calculate it, and the result was satisfactory. The results of the study show that BP artificial neural network in the appraisal of water quality has the advantages of simplicity and practical.

The Application of Artifical Neural Network in the Groundwater Quality Assessment in Industrial Park Catchment

By the theory and method of artificial neural network, a BP neural network model in groundwater quality evaluation is presented, with which groundwater quality in GuoBei mine is evaluated and compared with the classification of grey theoryThe result indicates that the BP neural network model can resolve primely complicated nonlinear relation between evaluating gene and water quality grade,and the method is convenient,reliable and precise, so it can be used commonly and objectively

Method of artificial neural network in groundwater quality evaluation

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Method of artificial neural network in groundwater quality evaluation