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The prediction performance of the GA-SVM model was evaluated by using a traditional SVM model with optimized grid-search-based parameters. The performance statistics of the two models are shown in Table 2. The computing time for the GA-SVM model is approximately half of that for the SVM model, but the prediction accuracy of the GA-SVM model is significantly better. These results suggest that the GA-SVM model provides improved feasibility and practicability compared to the SVM model.

Table 2

Prediction results of the GA-SVM compared to the traditional SVM

YearGA-SVM
Traditional SVM
R2Computing time (s)R2Computing time (s)
2009 0.83 1,029.26 0.67 2,062.52 
2013 0.85 1,026.64 0.67 2,061.74 
YearGA-SVM
Traditional SVM
R2Computing time (s)R2Computing time (s)
2009 0.83 1,029.26 0.67 2,062.52 
2013 0.85 1,026.64 0.67 2,061.74 

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