Research On Decision Support For Coordinate Development Of Energy-Economy-Environment Of Beijing-Tianjin-Hebei Area Based On 3E Big Data

The coordinated development of energy, economy and environment (3E) is the common global destination. Therefore, energy, economy and environment problems are always hot issues at home and abroad. However, conventional mathematics models and methods related with Energy-Economy-Environment (3E) analysis are almost based on statistical data, which aim at solving macro-planning problems. As the information technology develops, large varieties of heterogeneous data are collected, conventional mathematics models or methods are no longer applied for big data. Therefore it is urgent to find new models and methods. Besides, in order to satisfy the data processing and accessing requirements, technology framework of big data can be utilized such as Hadoop. Previous studies rarely focus on big data aspect, thus the research and work on analysis based on Energy-Economy-Environment decision support platform within big data framework is needed.This thesis first introduces current research status home and abroad on Energy-Economy-Environment problems, and then presents the design of Energy-Economy-Environment Decision Support Big Data Platform (3EBDSS). Based on this platform, introduces MapReduce based Aprori algorithm and uses it to find frequent patterns in 3E data, logistic regression analysis are carrying out later to predict air quality in Beijing, Tianjin and Heibei Province.