The Application Of The Data Mining Technologies Based On Association Rules In The Operation Optimization Of The Plant

A large number of datas are collected in the history database of the power plant. There islots of valuable information, which benefits to enhancing the economic performance andsafety of the power plant, hidden behind of the data.In this paper, data mining techniquesbased on the association rules are applied to make full use of the function of history datas soas to direct electric power production.Firstly, in this paper, the classical mining method on boolean association rules Apriori isstudied and compared with the improved algorithm AprioriTid as well as AprioriHybrid in thediversity of the time cost.Then the fuzzy association rules Fuzzy_Apriori is studied and usedto abstract rules from a automobile database which contains three fields namedmpg,horsepower and weight.Lastly,the fuzzy association rules algorithm based on clusteringis applied to abstract rules from the operation data in the boiler system of some plant and minethe target value of the flue gas oxygen content in some load.The target value accords with thequantitatively-calculated value and consequently demonstrates the efficiency that the datamining technologies based on association rules are applied to the plant's operationoptimization.