DocumentCode
442080
Title
Classified forgetting neural network and its effectiveness analysis
Author
Yan, Chang-Shun ; Li, Yi-Jun
Author_Institution
Sch. of Manage., Harbin Inst. of Technol., China
Volume
7
fYear
2005
fDate
18-21 Aug. 2005
Firstpage
4050
Abstract
The available classification method of neural network lacks the ability to deal with data of different variable time. Based on it, the paper puts the forgetting ideology into the classification method of neural network, and successfully brings up classified forgetting neural network model. In the end, the paper proves the effectiveness of using this model to classify random time changing data by experiment.
Keywords
data analysis; learning (artificial intelligence); neural nets; pattern classification; classified forgetting neural network; effectiveness analysis; forgetting coefficient; network training; random time changing data classification; Data analysis; Databases; Electronic mail; Error correction; Feedforward neural networks; Humans; Neural networks; Organizing; Technology management; Training data; Classified forgetting neural network; forgetting coefficient; network training;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location
Guangzhou, China
Print_ISBN
0-7803-9091-1
Type
conf
DOI
10.1109/ICMLC.2005.1527646
Filename
1527646
Link To Document