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A Weighted Fuzzy Time Series Forecasting Method Based on Clusters and Probabilistic Fuzzy Set

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Modeling, Simulation and Optimization

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 292))

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Abstract

Probabilistic fuzzy set (PFS) is an ideal tool to touch uncertainties due to randomness (probabilistic) and fuzziness (non-probabilistic) in a single framework. In the present study, we divide time series data into clusters and propose a novel weighted fuzzy time series (FTS) forecasting method using PFS. Proposed method models non-probabilistic uncertainty due to imprecision and linguistic representation of time series data and probabilistic uncertainties in assigning membership grades to time series datum along with occurrence of recurrence of fuzzy logical relations. In proposed forecasting method, probabilities to membership grades are assigned using Gaussian probability distribution function (PDF). Time series data of SBI share price are forecasted using proposed forecasting method in order to show its suitability and applicability. Root mean square error and average forecasting error are used as performance indicator to confirm the outperformance of proposed weighted fuzzy time series forecasting method based on PFS.

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Authors and Affiliations

  1. Department of Mathematics, Statistics and Computer Science, College of Basic Sciences and Humanities, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, 263145, India

    Krishna Kumar Gupta & Sanjay Kumar

Authors
  1. Krishna Kumar Gupta
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  2. Sanjay Kumar
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Corresponding author

Correspondence to Krishna Kumar Gupta .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, National Institute of Technology Silchar, Silchar, India

    Biplab Das

  2. Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, India

    Ripon Patgiri

  3. National Institute of Technology Silchar, Silchar, India

    Sivaji Bandyopadhyay

  4. Department of Automatics and Applied Software, “Aurel Vlaicu” University of Arad, Arad, Romania

    Valentina Emilia Balas

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Gupta, K.K., Kumar, S. (2022). A Weighted Fuzzy Time Series Forecasting Method Based on Clusters and Probabilistic Fuzzy Set. In: Das, B., Patgiri, R., Bandyopadhyay, S., Balas, V.E. (eds) Modeling, Simulation and Optimization. Smart Innovation, Systems and Technologies, vol 292. Springer, Singapore. https://doi.org/10.1007/978-981-19-0836-1_28

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