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Generic reconstruction technology based on RST for multivariate time series of complex process industries

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Abstract

In order to effectively analyse the multivariate time series data of complex process, a generic reconstruction technology based on reduction theory of rough sets was proposed. Firstly, the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology. Then, the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space, and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space. Finally, the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model. Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.

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Authors and Affiliations

  1. College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou, 412000, China

    Ling-shuang Kong  (孔玲爽)

  2. School of Information Science and Engineering, Central South University, Changsha, 410083, China

    Chun-hua Yang  (阳春华), Jian-qi Li  (李建奇), hong-qiu Zhu  (朱红求) & Ya-lin Wang  (王雅琳)

Authors
  1. Ling-shuang Kong  (孔玲爽)
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  2. Chun-hua Yang  (阳春华)
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  3. Jian-qi Li  (李建奇)
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  4. hong-qiu Zhu  (朱红求)
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  5. Ya-lin Wang  (王雅琳)
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Corresponding author

Correspondence to Ling-shuang Kong  (孔玲爽).

Additional information

Foundation item: Project(61025015) supported by the National Natural Science Funds for Distinguished Young Scholars of China; Project(21106036) supported by the National Natural Science Foundation of China; Project(200805331103) supported by Research Fund for the Doctoral Program of Higher Education of China; Project(NCET-08-0576) supported by Program for New Century Excellent Talents in Universities of China; Project(11B038) supported by Scientific Research Fund for the Excellent Youth Scholars of Hunan Provincial Education Department, China

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Kong, Ls., Yang, Ch., Li, Jq. et al. Generic reconstruction technology based on RST for multivariate time series of complex process industries. J. Cent. South Univ. Technol. 19, 1311–1316 (2012). https://doi.org/10.1007/s11771-012-1143-x

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  • DOI: https://doi.org/10.1007/s11771-012-1143-x

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