Title :
Neural Network Topological Evolvement
Author :
Zhongda, Yuan ; Zhen, Ye
Author_Institution :
Dept. of Comput. Sci., Tsinghua Univ., Beijing
Abstract :
In order to obtain instance response from evolving neural networks, we separate the evolving procedure and the output procedure in the traditional GA approach, and make them simultaneously. Thanks to the support from database system, this modified GA has three characteristics, namely serialized storage, persistent evolving and instance response to end user´s request. In our experiment, this approach shows off better performance over the conventional strategy
Keywords :
data mining; genetic algorithms; neural nets; data mining; genetic algorithm; neural network topological evolvement; serialized storage; Application software; Computer science; Data mining; Database systems; Electronic mail; Genetics; Multi-layer neural network; Neural networks; Neurons; Systems engineering and theory; Data Mining; Genetic Algorism; Neural Network;
Conference_Titel :
Computational Engineering in Systems Applications, IMACS Multiconference on
Conference_Location :
Beijing
Print_ISBN :
7-302-13922-9
Electronic_ISBN :
7-900718-14-1
DOI :
10.1109/CESA.2006.4281687
