Research And Implementation On Air Quality Forecasting Based On Data Mining

With the popularization of informationize in all sectors of society, and the rapid expansion of the technology of computer and database, a variety of application systems are constantly in use. These systems are producing more and more data. Therefore we face now can the question is how to gain the knowledge by modern methods and technology. Data mining, which aims at extracting novel and useful knowledge from large volumes of data, has emerged rapidly in last decades; it integrates techniques of machine leaning, statistic learning and database.Since 1983 Shanghai environment monitoring center has accumulated a mass of ambient air quality data, these data is of great value to us to know the changes of air quality. Nevertheless, for a very long time, this kind potential great strength has not been developed and utilized effectively and yet, has not played a positive and big role that it should. So Research of this discourse is in order to more productive use of these data.This thesis has discussed the design and implementation of the prediction model and implementation the self-adaptive base on data mining.Firstly, this thesis introduces the basic theory, main technology, methods and realization of data mining systemically. Secondly, the thesis describes the data analysis and the theory inferential reasoning process. And we also implement the ocular showing based on ArcGIS.Finally we design and realizing the module which discussed in this thesis based on J2EE. We also use the open source framework such as Spring and Hibernate, and we use RIA(Rich Internet Applications) as the way to show infonnation.