Research On Residential Areas Simultaneous Factor Prediction System Of Tianjin

Tianjin area is located in the developed coastal areas,is committing to the development of regional industry advantage.The trend of load growth is rapid,while the load structure of Tianjin area is relatively weak,can not meet the electric demand for capacity of long-term.Therefore,This paper presents a prediction method of community simultaneous factor based on artificial neural network,and develops simultaneous factor prediction system,provides a theoretical analysis and guidance for Tianjin distribution network planning.Through investigating and analysing all kinds of simultaneous factor,first determine the index system of simultaneous factors' influence.Get Tianjin's real residential area sample collection,do preprocessing of original indicator data,analyze the work simulation and calculation for the prediction model.Based on the idea of fuzzy clustering analysis,use fuzzy C means clustering algorithm,cluster analysis is performed on the sample set.The results show that,the classification model can clearly reflect the different sample from different residential and similarity,is conducive to a more accurate prediction of the coefficient of the next step.Then based on the artificial intelligence method,using the Elman neural network model,for each classification mode of samples do simulation and prediction analysis of simultaneous factor.The analysis results show that,Elman neural network can accurately predict the unknown samples' simultaneous factors,the training accuracy is higher than the traditional BP network model,and the rapid is convergence,meet the precision demand of Engineering.In view of the above prediction model of simultaneous factor,use Microsoft Visual C# language develop prediction system of Tianjin residential areas simultaneous factor.The basic function and the system can realize the prediction coefficients of different types of residential area,the interface is beautiful,the system can effectively guide the actual power grid construction projects,it has practical value.