The RMSE errors of validation and training data sets are also presented in Table 3. As reported in the table, the GA model employed here has decreased the RMSE error successfully for both significant wave height and peak spectral predictor models. The GA not only has decreased the RMSE error to 0.1533 m for the wave height predictor model but it has also improved the RMSE error for the peak spectral period predictor model to 0.2045 s in the best run. In the generation process, the population size of the GA for both predictor models is 400, the crossover fraction is 0.7, the number of elitism chromosomes is 20, and the remaining children are taken for the mutation process. The obtained validation errors for both predictor models are, respectively, 0.2911 m and 0.3461 s. The obtained results in this part show the combined GA and FIS models' efficiency to predict wave parameters, although final evaluation of the developed models is related to their evaluation versus the testing data never used during the training process.