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RBF) neural network were trained to estimate the diameter of machined holes. The multisensory approach includes an acoustic emission sensor, accelerometer, dynamometer and an electric power sensor. The optimum configuration for each artificial intelligence system was determined based on algorithms designed to examine the influence of each system's signals and specific parameters on the final result of the estimate. The results indicated the MLP ANN was more robust in withstanding datadoi:10.1007/s40430-016-0525-7 fatcat:t6svdkytincsdaxgfstvqxhcnu