Advances in Neural Networks – ISNN 2007: 4th International - download pdf or read online

By Nan Jiang, Yixian Yang, Xiaomin Ma, Zhaozhi Zhang (auth.), Derong Liu, Shumin Fei, Zengguang Hou, Huaguang Zhang, Changyin Sun (eds.)

ISBN-10: 3540723943

ISBN-13: 9783540723943

ISBN-10: 3540723951

ISBN-13: 9783540723950

This e-book is a part of a 3 quantity set that constitutes the refereed complaints of the 4th overseas Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007.

The 262 revised lengthy papers and 192 revised brief papers provided have been rigorously reviewed and chosen from a complete of 1,975 submissions. The papers are geared up in topical sections on neural fuzzy keep an eye on, neural networks for keep watch over functions, adaptive dynamic programming and reinforcement studying, neural networks for nonlinear structures modeling, robotics, balance research of neural networks, studying and approximation, information mining and have extraction, chaos and synchronization, neural fuzzy platforms, education and studying algorithms for neural networks, neural community buildings, neural networks for development attractiveness, SOMs, ICA/PCA, biomedical functions, feedforward neural networks, recurrent neural networks, neural networks for optimization, help vector machines, fault diagnosis/detection, communications and sign processing, image/video processing, and functions of neural networks.

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Read Online or Download Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part III PDF

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Additional info for Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part III

Example text

The structure of the paper is as follows: firstly, the background and problem will be introduced. Secondly, NIHSS and TCM-SSASD will be standardized and combined. Based on it, three kinds of BP neural networks will be built to approximate the relationship of them. The algorithms and improving schemes will be presented in the third sections, including the design of four BP algorithms and two multiple models schemes. In the fourth section, a simulation result will be given out based on clinic data.

ISNN 2007, Part III, LNCS 4493, pp. 26–34, 2007. © Springer-Verlag Berlin Heidelberg 2007 Application of BPNN to Power Transformer Insulation Diagnosis 27 patterns is of importance for the diagnosis of the quality of power transformers. PD behavior can be represented in various ways. , the PD pattern is described using a pulse count N versus pulse height Q and phase angle φ diagram. Previous experimental results have adequately demonstrated that φ-Q-N distributions are strongly dependent upon PD sources, therefore, the 3-D patterns can be used to characterize insulation defects [4].

References 1. : Modern Power Transformer Practice. John Wiley & Sons (1979) 2. : PD Pattern Analysis During Induced Test of Large Power Transformers. IEEE Trans. Dielectrics and Electrical Insulation 7 (2000) 95–101 3. : Change in PD Pattern with Aging. IEEE Trans. Dielectrics and Electrical Insulation 11 (2004) 13–18 4. : Automated Recognition of Partial Discharge. IEEE Trans. on Dielectrics and Electrical Insulation 2 (1995) 796-821 5. : A Fuzzy Information Approach to Integrating Different Transformer Diagnostic Methods.

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Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part III by Nan Jiang, Yixian Yang, Xiaomin Ma, Zhaozhi Zhang (auth.), Derong Liu, Shumin Fei, Zengguang Hou, Huaguang Zhang, Changyin Sun (eds.)


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