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Substation Intelligent Monitoring System Based on Pattern Recognition

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 225))

Abstract

Pattern recognition technology is a new intelligent science with a wide range of applied. It can be applied in a variety of intelligent control and monitoring areas. According to the technical characteristics of pattern recognition, it can be used in substations video surveillance system. Tests show that this control method can effectively deal with the increasing workload of the substation monitoring of tasks, but can also greatly improve the control accuracy and reduce cost. This paper briefly discusses the basic principles of pattern recognition, and then introduces some commonly used pattern recognition method, And applies them to the specific substation control and inspection process respectively.

This work is worded for pattern recognition in the field of Substation Intelligent Monitoring System.

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References

  1. Bian, z.: Pattern Recognition (Second edition). Tsinghua University Press, BeiJing (2002)

    Google Scholar 

  2. Wald, A.: Contributions tO the theory of statistical estimation and testing of hypotheses. Annals of Math-ematieal Statistics 10, 299–326 (1939)

    Article  MathSciNet  MATH  Google Scholar 

  3. Wang, Q., et al.: A fast template matching target recognition algorithm[J]. Computer Engineering and Applications 6, 42–43, 49 (2000)

    Google Scholar 

  4. Meng, B., et al.: Feedforward neural networks in an improved BP algorithm. Southeast University press(Natural Science) 31(4), 40–42 (2001)

    Google Scholar 

  5. Liu, Y., You, Z.: For Image Object Recognition and Neural Network Applications Vehicle Identification. Computer engineering 29(3), 30–32 (2003)

    Google Scholar 

  6. Zhang, J., Yang, S., et al.: Pattern Recognition in Remote Video Monitoring System Substation Applied Research. Power Systems 26(12), 50–53 (2007)

    Google Scholar 

  7. Chang, X., Feng, X.: Based on background subtraction and temporal entropy new method of moving target detection. Computer Simulation 25(3), 235–238 (2008)

    MathSciNet  Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Liu, S., Xu, X. (2011). Substation Intelligent Monitoring System Based on Pattern Recognition. In: Zeng, D. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23220-6_60

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  • DOI: https://doi.org/10.1007/978-3-642-23220-6_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23219-0

  • Online ISBN: 978-3-642-23220-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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