| With the development of environmental information and data mining technology, the application of data mining will be faced with more opportunities and challenges in environmental supervisor. Especially it is raised in the environmental protection enforcement law that supervision of pollutants needs achieve "two changes". The "two changes" includes changing from the end to the process and changing from supervisor to service. Flue gas desulfurization monitor is a very important supervisor means. And the data in Flue gas desulfurization monitor has the character of large quantity, complexity and timely high, so it has become an important content in data mining that how to deal with these data, and make these data better service to the safe operation of pollution control facilities and reduce the pollutant emission. Association rule technology in data mining can effectively find linkage in large data. Therefore, the research on association rule data mining in automatic monitoring of the environment is now becoming an important research direction.First of all in this paper, it is introduced the data mining technology, and it includes characteristic, process, algorithm and its application. Then it is talked about the realization of the association rule technology in data mining. It is mainly disused the algorithm and concept about association rule technology. And then through analysis the attribute and characteristic, we establish the model of flue gas desulfurization monitor. From the model we can see the association rule is adapted to the analysis. At last we preprocess the large raw data and extract the important data that we need focus on. We use these data establish fluctuations model, parameter chromosome model and forecast model based on association rule. It is proved that the model meet to the actual requirements through the experiment and analysis. The model can take good effect in flue gas desulfurization monitor. |
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