Design classification algorithm in data mining prototype system and application in unit's bidding ability of electricity market

Authors:
Hongwen Yan;Rui Ma
Affiliations:
Changsha University of Science and Technology, Changsha, China;Changsha University of Science and Technology, Changsha, China
Venue:
AEE'06 Proceedings of the 5th WSEAS international conference on Applications of electrical engineering
Year:
2006

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Abstract

Design and implementation of classification algorithm in data mining prototype system is described in this paper. This function analyzes a set of training data, constructs a model for each class based on the features in the data, and adjusts the model based on the test data. The architecture of data mining prototype system is defined and the algorithms including ID3, C4.5, SLIQ and Bayesian is discussed. A method based on Naive Bayesian classification is applied to the generation unit's bidding decision system of electricity market. The knowledge that the ability of unit bidding is gained, Taking the market's demand, bidding price and the capacity of bidding unit into consideration. This knowledge is very useful in supporting the generating bidding unit to make decisions and the electric agency, PX and ISO to design an optimal trade project.