DocumentCode :
690236
Title :
A recognition method of surface -water based on RBF neural network
Author :
Chen Xue-lian ; Hu Jing-tao
Author_Institution :
Dept. of Inf. Service & Intell. Control, Shenyang Inst. of Autom., Shenyang, China
fYear :
2013
fDate :
15-17 Nov. 2013
Firstpage :
217
Lastpage :
221
Abstract :
For the extraction of surface-water data characteristics was not easily, and pseudo-depression was easy to confuse with the surface-water in the recognition of surface-water, surface-water radial basis function neural network recognition model was proposed. According to the features of surface-water and the computational result as input and output neural cells, the surface-water radial basis function neural network recognition model was established. The proposed model solved the problem that the distinguishing of surface-water and pseudo-depression was difficult. As the results, the proposed surface-water recognition model can recognize the surface-water efficiently.
Keywords :
digital elevation models; geophysics computing; pattern classification; radial basis function networks; RBF neural network; surface-water radial basis function neural network recognition model; surface-water recognition method; Artificial neural networks; Character recognition; Computational modeling; Lakes; RBF neutral network; potential outlet; recognition of surface-water;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics Information and Emergency Communication (ICEIEC), 2013 IEEE 4th International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/ICEIEC.2013.6835491
Filename :
6835491
Link To Document :
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