"Binary Classification of Ground Vehicles Based on the Acoustic Data Using Fuzzy Logic Rule-Based Classifiers"

by Hongwei Wu and Jerry M. Mendel

July 2002

We carried out the leave-one-out and leave-M-out experiments to evaluate the performance of all classifiers. In the leave-one-out experiments, only one run was used for testing, and all the other runs were used for training. In the leave-M-out experiments, one run of each kind of vehicle was used for testing, and all the other runs were used for training. Our experiments showed that for each binary classification problem, both the type-1 and type-2 FL-RBCs had significantly better performance than the Bayesian classifier, whereas the type-1 and type-2 FL-RBCs had similar performance, although most of the time, the type-2 FL-RBC had slightly better performance than the type-1 FL-RBC.

Both the type-1 and type-2 FL-RBC designs were tested for blind runs of the normal terrain. The blind test results of the type-2 FL- RBC designs were scored by our sponsor at the Army Research Laboratory. The scores were very high, which demonstrates that our type-2 FL-RBC designs for the binary classification of ground vehicles based on their acoustic emissions are successful.

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