DocumentCode
2628995
Title
Research of Wavelet Neural Network Model Based on Extenics
Author
Wang, Hong ; Yu, Yongquan ; Zhu, Xiaoyuan
Author_Institution
Guang Dong Univ. of Technol., Guangzhou
fYear
2007
fDate
21-23 Nov. 2007
Firstpage
2024
Lastpage
2029
Abstract
In order to conquer the disadvantage of the traditional wavelet neural networks (WNN), the paper presents WNN model which is based on extenics. The model uses the feature number of matter element to determine the volume of importation of neuron number, makes sure the number of output neurons based on identification the type number needed, and makes a correct judgment about the neurons inhibit or activation. It optimizes the structure design of wavelet neural network. Then there is an experiment about the weather prediction using the new model. Experimental results show that the new model has better convergence and accuracy.
Keywords
feedforward neural nets; wavelet transforms; weather forecasting; extenics theory; matter element theory; neuron number; wavelet neural network model; weather prediction; Artificial neural networks; Computer networks; Convergence; Design optimization; Feedforward neural networks; Information technology; Neural networks; Neurons; Set theory; Weather forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Convergence Information Technology, 2007. International Conference on
Conference_Location
Gyeongju
Print_ISBN
0-7695-3038-9
Type
conf
DOI
10.1109/ICCIT.2007.21
Filename
4420550
Link To Document