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Evaluation of multivariate transductive neuro-fuzzy inference system for multivariate time-series analysis and modelling

Published:28 December 2020Publication History

ABSTRACT

Multivariate Transductive Neuro-Fuzzy Inference System model, named the mTNFI is a previously proposed conceptual transductive approach designed for analysis and modelling of multivariate time-series data. In this study, we revisit, implement and evaluate the mTNFI model potential for patterns of relationship extraction from a collection of interrelated time-series data. Results of conducted assessment confirm the mTNFI capability in recognizing patterns of relationship and then to model them in human-readable form, i.e. fuzzy rules. Additionally, a comparative analysis also show the superiority of the mTNFI model in comparison to other widely known time-series forecasting techniques when being used to predict future values.

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      cover image ACM Other conferences
      SIET '20: Proceedings of the 5th International Conference on Sustainable Information Engineering and Technology
      November 2020
      277 pages
      ISBN:9781450376051
      DOI:10.1145/3427423

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      Publication History

      • Published: 28 December 2020

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      SIET '20 Paper Acceptance Rate45of57submissions,79%Overall Acceptance Rate45of57submissions,79%

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