Title :
Data Mining Based on Clonal Selection Wavelet Network
Author_Institution :
North China Inst. of Sci. & Technol., Beijing
fDate :
July 30 2007-Aug. 1 2007
Abstract :
Recently there has been significant development in the use of wavelet network methods in various data mining processes, but how to select the proper structure and parameter of wavelet network is a difficulty. This paper offers a kind of solution, in which the clonal selection algorithm is proposed and the hierarchical structure is used in the coding scheme, thus a novel algorithm of clonal selection wavelet network is presented, meanwhile the evolution of topologic structure and the parameter learning of the wavelet network can be gotten. To evaluate the performance we apply this algorithm to data mining. After illustrating our method with a representative dataset, simulations show that the data mining based on clonal selection wavelet network achieves the better prediction accuracy than other traditional methods.
Keywords :
artificial immune systems; data mining; learning (artificial intelligence); neural nets; clonal selection; coding scheme; data mining; parameter learning; topologic structure; wavelet network; Artificial intelligence; Classification tree analysis; Computer science; Data mining; Databases; Distributed computing; Electronic mail; Feedforward neural networks; Neural networks; Software engineering;
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-0-7695-2909-7
DOI :
10.1109/SNPD.2007.245