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- W4379144567 abstract "This study investigates the ability of a new hybrid neuro-fuzzy model by combining the neuro-fuzzy (ANFIS) approach with the marine predators’ algorithm (MPA) in predicting short-term (from 1 h ahead to 1 day ahead) significant wave heights. Data from two stations, Cairns and Palm Beach buoy, were used in assessing the considered methods. The ANFIS-MPA was compared with two other hybrid methods, ANFIS with genetic algorithm (ANFIS-GA) and ANFIS with particle swarm optimization (ANFIS-PSO), in predicting significant wave height for multiple lead times ranging from 1 h to 1 day. The multivariate adaptive regression spline was investigated in deciding the best input for prediction models. The ANFIS-MPA model generally offered better accuracy than the other hybrid models in predicting significant wave height in both stations. It improved the accuracy of ANFIS-PSO and ANFIS-GA by 8.3% and 11.2% in root mean square errors in predicting a 1 h lead time in the test period." @default.
- W4379144567 created "2023-06-03" @default.
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- W4379144567 date "2023-06-01" @default.
- W4379144567 modified "2023-10-14" @default.
- W4379144567 title "Improving Significant Wave Height Prediction Using a Neuro-Fuzzy Approach and Marine Predators Algorithm" @default.
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- W4379144567 doi "https://doi.org/10.3390/jmse11061163" @default.
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