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Handling Forecasting Problems Based on Two-Factor High-Order Fuzzy Time Series and Particle Swarm Optimization

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Advances in Engineering Research and Application (ICERA 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 104))

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Abstract

In real time, an observation series can depend on and be affected by many different observations. Therefore, to forecast more accurately, it is necessary to consider adding multi factors that have potential correlations in the model. This study proposes a new forecasting model based on two - factor high - order fuzzy time series (FTS) combined with particle swarm optimization (PSO) for forecasting the daily average temperature and forecasting car road accidents. Different from some previous models, in the proposed model, time - variant high-order fuzzy logical relationship groups are built to be used in the forecasting process. While, PSO is still used to find the optimal interval in the universe of discourse of each factor. Two data sets of weather temperatures and annual road traffic accidents with corresponding factors “Temperature”, “Cloud density” and “Killed”, “Mortally wounded”, respectively are selected to demonstrate the effectiveness of the proposed model and compare it with existing models. The experimental results show that the proposed model has better forecasting accuracy than previous forecasting models based on two-factor high-order FTS.

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Authors and Affiliations

  1. University of Technology, Thai Nguyen, Vietnam

    Nghiem Van Tinh & Nguyen Tien Duy

Authors
  1. Nghiem Van Tinh
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  2. Nguyen Tien Duy
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Corresponding author

Correspondence to Nghiem Van Tinh .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Automation, TU Ilmenau, Ilmenau, Thüringen, Germany

    Kai-Uwe Sattler

  2. Faculty of Electronic Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Duy Cuong Nguyen

  3. Faculty of Mechanical Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Ngoc Pi Vu

  4. Hanoi University of Science and Technology, Hanoi, Vietnam

    Banh Tien Long

  5. Institute for Automation and Systems Engineering, TU Ilmenau, Ilmenau, Thüringen, Germany

    Horst Puta

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Tinh, N.V., Duy, N.T. (2020). Handling Forecasting Problems Based on Two-Factor High-Order Fuzzy Time Series and Particle Swarm Optimization. In: Sattler, KU., Nguyen, D., Vu, N., Tien Long, B., Puta, H. (eds) Advances in Engineering Research and Application. ICERA 2019. Lecture Notes in Networks and Systems, vol 104. Springer, Cham. https://doi.org/10.1007/978-3-030-37497-6_45

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