Time series forecasting using a TSK fuzzy system tuned with simulated annealing

ALMARAASHI, Majid, JOHN, Robert, COUPLAND, Simon and HOPGOOD, Adrian (2010). Time series forecasting using a TSK fuzzy system tuned with simulated annealing. In: IEEE International Conference on Fuzzy Systems (FUZZ), 2010. IEEE xplore, 1-6.

[img]
Preview
PDF
fuzz-ieee2010.pdf - Accepted Version

Download (152kB) | Preview
Official URL: http://dx.doi.org/10.1109/FUZZY.2010.5584523
Link to published version:: https://doi.org/10.1109/FUZZY.2010.5584523
Related URLs:

    Abstract

    In this paper, a combination of a Takagi-Sugeno fuzzy system (TSK) and simulated annealing is used to predict well known time series by searching for the best configuration of the fuzzy system. Simulated annealing is used to optimise the parameters of the antecedent and the consequent parts of the fuzzy system rules. The results of the proposed method are encouraging indicating that simulated annealing and fuzzy logic are able to combine well in time series prediction.

    Item Type: Book Section
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Mobile Machine and Vision Laboratory
    Identification Number: https://doi.org/10.1109/FUZZY.2010.5584523
    Page Range: 1-6
    Depositing User: Adrian Hopgood
    Date Deposited: 31 Aug 2012 13:09
    Last Modified: 18 Mar 2021 13:49
    URI: http://shura.shu.ac.uk/id/eprint/5635

    Actions (login required)

    View Item View Item

    Downloads

    Downloads per month over past year

    View more statistics