| As the electric power enterprise automation level unceasingenhancement, the power plant in the production management informationconstruction also had great progress. SIS system (Supervisory informationsystem) as an indispensable modern power plant production managementsystem, also put on the high-speed development of the agenda. SIS systemwill be the DCS system (Distributed control system) equipment real-time datathrough the various interface software collection to the database, save for theunity of the data format for the power plant, the magnitude of the operationdata accumulated, and faced with increasingly large database, how to efficientand into the database to extract the knowledge and the law has become animportant task.Data mining technology matures, Provides a way to solve the aboveproblem. This article focuses on the decision tree C4.5algorithm is studied,and in relation to the algorithm to be improved, Through simulationexperiment, to achieve the desired effect. The paper through to the SIS construction, introduces the application ofthe system database type selection, composition and function of the softwareand hardware architecture. In view of the above problems, the papercombined with the characteristics of electric power industry., data mining,decision tree algorithm as the basis of theoretical research, the data miningtechniques applied to the power plant SIS system applications. Byconstructing a decision tree model to analyze the results of the excavation,evaluation, found hidden in the massive data behind the law. Meanwhile, theimproved algorithm simulation results were analyzed. Through data miningtechnology, effective in optimizing the operation of the power plant and faultdiagnosis to guide the work, so as to Power Plant safety production and crewstability, economic operation to provide important decision support to helppower companies in the growing competition in the market to gain acompetitive advantage. |
PDF Full Text Request