Download Advances in Neural Network Research and Applications by Chen-Feng Wu, Yu-Teng Chang, Chih-Yao Lo, Han-Sheng Zhuang PDF

By Chen-Feng Wu, Yu-Teng Chang, Chih-Yao Lo, Han-Sheng Zhuang (auth.), Zhigang Zeng, Jun Wang (eds.)

This e-book is part of the complaints of the 7th foreign Symposium on Neural Networks (ISNN 2010), hung on June 6-9, 2010 in Shanghai, China. ISNN 2010 bought a variety of submissions from approximately hundreds of thousands of authors in approximately forty international locations and areas throughout six continents . in accordance with the rigorous peer-reviews by way of this system committee individuals and the reviewers, 108 top of the range papers have been chosen for guides in Lecture Notes in electric Engineering (LNEE) lawsuits. those papers disguise all significant subject matters of the engineering designs and purposes of neural community learn. as well as the contributed papers, the ISNN 2010 technical application integrated 4 plenary speeches via Andrzej Cichocki (RIKEN mind technological know-how Institute, Japan), Chin-Teng Lin (National Chiao Tung collage, Taiwan), DeLiang Wang (Ohio nation college, USA), Gary G. Yen (Oklahoma country collage, USA).

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5 ∑ t =1 7. 25 [g t ( x ) − yt ]2 (8) If E < E max (one positive value has be preset) or it gets the maximum train epochs, then stop training; else order E=0, return to step (2). 4 The Prediction Model Simulation Prepare oil samples with calibration water content using artificial ration, and then use the three-phase flow dynamic mixed devices to simulate the actual oil well. According to the nonlinear mapping relation between the water content and its influencing factors, taking the frequencies of the coaxial line water detector based on phase and the measured value of the turbine flowmeter as the input vectors of the WNN, taking corresponding known water content in crude oil as the output vector.

Chinese Journal of Scientific Instrument 23(1), 75–76 (2002) 5. : Fhase measurement of water content in oil well. J. Journal of Harbin Institute of Technology 34(2), 245–247 (2002) 6. : Test Study of Water Cut Tool in Oil Well Based on Phase Method. Acta Metrologica Sinica 25(4), 366–368 (2004) 7. : Simulation and Application of MATLAB Neural Network. Science Press (2003) 8. : Artifical Neural Network Course Book. cn Abstract. In order to improve prediction accuracy of urban heat island intensity, we chose 9 main influencing factors from 1981 to 2006 and predicted urban heat island intensity in Chuxiong city in 2006 with backpropagation neural network.

Wu et al. Actual Value Predict at t-1 Predict at t-2 Predict at t-3 Time series data for utilization (occupation case-2) 100 90 Utilization 80 70 60 50 40 00 :1 9 00 :1 7 00 :1 8 00 :1 6 00 :1 4 00 :1 5 00 :1 3 00 :1 1 00 :1 2 00 :1 0 00 :0 9 00 :0 7 00 :0 8 00 :0 6 00 :0 4 00 :0 5 00 :0 3 00 :0 1 00 :0 2 00 :0 0 30 Time Fig. 5. The simulation result for system utilization of occupation case Actual Value Predict at t-1 Predict at t-2 Predict at t-3 Time series data for utilization (random case) oatin iliztU 100 90 80 70 60 50 40 30 20 10 0 :00 00 :01 00 :02 00 :03 00 :04 00 :05 00 :06 00 :07 00 :08 00 :09 00 :10 00 Time :11 00 :12 00 :13 00 :14 00 :15 00 :16 00 :17 00 :18 00 :19 00 Fig.

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