Feature Subset Selection for Driving Forces of Cultivated Land Based on PSO-SVM

The particle swarm optimization(PSO) has the character of the high implementing speed.It is little affected by dimension.The support vector machines(SVM) is based on the theory of structural risk minimization.Combining the binary particle swarm optimization(BPSO) and the SVM,the feature subset selection for driving forces of cultivated land is constructed.This method uses the features defined in the feature subset to train the SVM which is evaluated by fitness fuction.The result of fitness fuction is utilized to direct the BPSO to search.The case study shows that this method has the excellent efficiency to select the feature subset.