The CMAC based FLC and its application to rear-loading truck problems

In this paper, the CMAC-based FLC is applied to rear-loading truck problems. We show that the proposed CMAC-based FLC has fast learning capability in forward and backward computations because it possesses the local generalization and because it has only a small number of activated units (hypercubes) in the network. Simulation results validate the fast learning and the accurate approximation of the proposed CMAC-based FLC.

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