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Evolving Fuzzy Prediction Intervals in Nonstationary Environments | IEEE Journals & Magazine | IEEE Xplore

Evolving Fuzzy Prediction Intervals in Nonstationary Environments


Abstract:

This work aims at designing a novel evolving fuzzy prediction interval able to model nonlinear time-variant systems. To achieve this goal, we integrate a passive mechanis...Show More

Abstract:

This work aims at designing a novel evolving fuzzy prediction interval able to model nonlinear time-variant systems. To achieve this goal, we integrate a passive mechanism meant to update the model when new data are available with an active mechanism able to trigger ad-hoc adaptation mechanisms when changes are detected in the data-generating process. The base model considered for this proposal was the prediction interval based on fuzzy numbers, which allow handling the characterization of the uncertainty of a system through additional parameters focused on the computation of the interval width. The performance of the proposed solution has been tested on both synthetic and real data. In this work, the synthetic data was generated from a generic nonlinear time-variant system, while the real data correspond to measurements of solar power generation obtained from photovoltaic panels. The simulation results confirm the effectiveness of the proposed evolving fuzzy prediction interval for modeling systems that present changes in their dynamics over time.
Page(s): 903 - 916
Date of Publication: 26 July 2023
Electronic ISSN: 2471-285X

Funding Agency:


References

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