DocumentCode :
2903679
Title :
A new growing self-organizing neuron-fuzzy network with application to wastewater treatment
Author :
Jun-fei, Qiao ; Hong-gui, Han
Author_Institution :
Coll. of Electron. & Control Eng., Beijing Univ. of Technol., Beijing
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
525
Lastpage :
530
Abstract :
A new neural fuzzy algorithm based on the method of growing self-organizing network is proposed in this paper. Then the fuzzy rules can be changed on-line, it takes the experience out of the necessary side for the number of the fuzzy rules. A novel learning algorithm based on dynamic descent gradient is also presented. The main salient characters of the algorithm in this paper are: 1) a new method resolves the problem of the conventional neural network which canpsilat change the structure of the network; 2) the neurons of the neural network can be changed on-line; 3) a new method for the fast learning speed can be own. This new algorithm can be used to control the dissolved oxygenic in the wastewater treatment process. The results of the experiments prove the superiority of this algorithm compared with the conventional neural fuzzy algorithm.
Keywords :
environmental science computing; fuzzy neural nets; learning (artificial intelligence); self-organising feature maps; wastewater treatment; fuzzy rules; growing self-organizing network; neural fuzzy algorithm; novel learning algorithm; wastewater treatment; Fuzzy systems; Wastewater treatment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1098-7584
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2008.4630418
Filename :
4630418
Link To Document :
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