Apriori Algorithm And Its Application In Intelligent Village Electricity Analysis Research

With the national electricity grid company deeply intelligent construction anddevelopment,Intelligent capture devices in people’s daily life gradually spread, howefficient use of these data, convert it to a useful auxiliary power grid enterprisesknowledge market analysis and decision-making is needed to solve the problem at thisstage. Data mining can be found hidden in the relationship between the large amounts ofdata,therefore, we chose to use the association rule mining method, the residents of smartpower data to analyze, dig out the various factors that influence the level of impact of thelaw on electricity consumption data.This paper introduces the theory of data mining and data mining methods, thetraditional frequent itemsets generation algorithm Apriori algorithm analysis, theresidential electricity consumption data for the selected features and shortcomings existApriori is designed to improve the ideological matrix based on Boolean and reducetransactional database from several scale pruning step and connection optimization stepoperation of the algorithm has been optimized through experiments show that thismethod can effectively improve the efficiency of the algorithm. at the same time, alsostudied the application status of data mining technology in smart power analysis stage,analyzes the main factors affecting the residents with electricity, the final selection ofempirical data of electricity Beijing Lotus Park District residents, optimized Apriorialgorithm applied research is completed.