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Improved Grey Relational Analysis for Model Validation

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Methods and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1094))

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Abstract

GRA (Grey Relational Analysis) is a typical time series similarity analysis method. However in model validation, it cannot satisfy the feature of monotonicity, and the result is lack of precision. Based on several similarity measurement criteria of time series data, traditional GRA method is developed and modified to satisfy normalization, symmetry and monotonicity. Case study shows that, improved GRA can produce a better similarity analysis result, which is in accordance with the result of TIC (Theil’s Inequality Coefficient).

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Authors and Affiliations

  1. Harbin Institute of Technology, Harbin, 150001, China

    Ke Fang, Yuchen Zhou & Ju Huo

Authors
  1. Ke Fang
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  2. Yuchen Zhou
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  3. Ju Huo
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Corresponding author

Correspondence to Ke Fang .

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Editors and Affiliations

  1. National University of Singapore, Singapore, Singapore

    Gary Tan

  2. Universität der Bundeswehr München, Neubiberg, Germany

    Axel Lehmann

  3. National University of Singapore, Singapore, Singapore

    Yong Meng Teo

  4. Nanyang Technological University, Singapore, Singapore

    Wentong Cai

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Fang, K., Zhou, Y., Huo, J. (2019). Improved Grey Relational Analysis for Model Validation. In: Tan, G., Lehmann, A., Teo, Y., Cai, W. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2019. Communications in Computer and Information Science, vol 1094. Springer, Singapore. https://doi.org/10.1007/978-981-15-1078-6_21

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  • DOI: https://doi.org/10.1007/978-981-15-1078-6_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1077-9

  • Online ISBN: 978-981-15-1078-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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