DocumentCode :
1897634
Title :
BP Neural Network with Error Feedback Input Research and Application
Author :
Wan, Dingsheng ; Hu, Yuting ; Ren, Xiang
Author_Institution :
Coll. of Comput. & Inf. Eng., HoHai Univ., Nanjing, China
Volume :
1
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
63
Lastpage :
66
Abstract :
Traditional data mining algorithm had limited capacity at short-term hydrological forecasting with low accuracy, and made little use of the error between the data set and the results to correct the results. Considering of the traditional hydrology predictive algorithm combined only with the external associated factors, but had not fully excavated the predictive data itself, the BP neural network predictive algorithm with error feedback input was proposed. Because the algorithm makes full use of the relationship between the forecasting result and the system information entropy, it makes the forecasted results more accurate, and achieves a satisfied result.
Keywords :
backpropagation; data mining; entropy; forecasting theory; geophysics computing; hydrology; BP neural network; data mining algorithm; error feedback input research; hydrology predictive algorithm; short-term hydrological forecasting; system information entropy; Computer errors; Computer networks; Data mining; Error correction; Information entropy; Input variables; Mutual information; Neural networks; Neurofeedback; Random variables; Data mining; Feedback input; Neural network; Self-iterative back-propagation; System information entropy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.24
Filename :
5287706
Link To Document :
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