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Model Recognition Orientated at Small Sample Data

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Fuzzy Information & Engineering and Operations Research & Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 211))

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Abstract

System modeling is a prerequisite to understand object properties, while the chances are that an industrial site may come along with restricted conditions, leading to less experimental data acquired about the objects. In this case, the application of traditional statistical law of large numbers for modeling certainly will influence the identification precision. Aiming at the problems in recognition of small samples being not that high in precision, it is proposed to introduce the bootstrap-based re-sampling technique, upon which the original small sample data are expanded in order to meet the requirements of the statistical recognition method for sample quantity, so as to meet the requirements of precision. The simulation results showed that the extended sample model recognition accuracy is substantially higher than that of the original small sample. This illustrates the validity of the bootstrap-based re-sampling technique, working as an effective way for small sample data processing.

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Acknowledgments

The work is supported by Chongqing Educational Committee Science and Technology Research Project No.KJ091402, No.  KJ111417, and the Natural Science Foundation of Chongqing University of Science & Technology No.CK2011Z01.

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Authors and Affiliations

  1. School of Electric and Information Engineering, Chongqing University of Science and Technology, Chongqing, 401331, China

    Jun-ling Yang, Yan-ling Luo & Ying-ying Su

Authors
  1. Jun-ling Yang
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  2. Yan-ling Luo
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  3. Ying-ying Su
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Corresponding author

Correspondence to Jun-ling Yang .

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Editors and Affiliations

  1. School of Mathematics and Information Science, Guangzhou University Higher Education Mega Center, Guangzhou, People's Republic of China

    Bing-Yuan Cao

  2. Department of Mathematics and Computer Sciences, Mazandaran University, Babolsar, Iran

    Hadi Nasseri

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Yang, Jl., Luo, Yl., Su, Yy. (2014). Model Recognition Orientated at Small Sample Data. In: Cao, BY., Nasseri, H. (eds) Fuzzy Information & Engineering and Operations Research & Management. Advances in Intelligent Systems and Computing, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38667-1_30

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  • DOI: https://doi.org/10.1007/978-3-642-38667-1_30

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38666-4

  • Online ISBN: 978-3-642-38667-1

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