Data mining method and case analysis of building energy demand side management

Briefly presents four common data mining techniques and evaluates them based on related studies of building load classification and prediction. Analyses the electricity data of a residential community in Shanghai by means of K mean clustering algorithm, and the result shows a high degree of consistency between the clustering analysis and statistical method using the K mean algorithm combining with the data mined and the actual situation, and more accurate and reliable than the results of logical reasoning.