Application on Selecting Simultaneous Factor of City Community Based on Data Mining

Abstract:

Selecting simultaneous factor is the basis for the power system load forecasting reasonably. Presently, the simultaneous factors selection is lack of theoretical basis, selecting results cant match the actual electricity demand of community reasonably. Accordingly, this paper presents a method for determining simultaneous factor of city community based on data mining. By analyzing the main factor of city communitys simultaneous factor, construct index system of simultaneous factors influencing factor. Establish the fuzzy membership function to do the unified quantization of qualitative indexes and standardization, do cluster analysis with the treated samples based on fuzzy K-means clustering algorithm, according to the clustering results predict new samples simultaneous factor. The actual examples show that, this methods selection principle of simultaneous factor is more systematic and scientific, the results are more significant for the distribution network planning of practical city community.

• Periodical: Applied Mechanics and Materials (Volumes 513-517)
• Pages: 1421-1424
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.513-517.1421
• Online since: February 2014
• Authors: Wei Ji*, Qing Xie, Hong Wei Zhang, Wei Tao Hu, Fang Cheng Lü
• Keywords: Data Mining (DM), Distribution Network Planning, K-Means Clustering, Simultaneous Factor

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