Application of the hybrid ANFIS models for long term wind power density prediction with extrapolation capability

Monowar Hossain, Saad Mekhilef, Firdaus Afifi, Laith M. Halabi, Lanre Olatomiwa, Mehdi Seyedmahmoudian, Ben Horan, Alex Stojcevski
  • PLoS ONE, April 2018, Public Library of Science (PLoS)
  • DOI: 10.1371/journal.pone.0193772

Wind power density prediction

What is it about?

In this paper, the suitability and performance of ANFIS (adaptive neuro-fuzzy inference system), ANFIS-PSO (particle swarm optimization), ANFIS-GA (genetic algorithm) and ANFISDE (differential evolution) has been investigated for the prediction of monthly and weeklywind power density (WPD) of four different locations.

Why is it important?

The results obtained from ANFIS-PSO and ANFIS-GA enjoy higher performance and accuracy than other models, and they can be suggested for practical application to predict monthly and weekly mean wind power density.

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The following have contributed to this page: Dr Lanre Olatomiwa