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In this paper, four data-driven classification approaches, that is, K-nearest neighbors (K-NN), self-organizing map (SOM), multi-layer perceptron (MLP), and Bayesian Network classifier (BNC), are applied to a health condition monitoring problem for the wearing cutter. The dataset is produced from a cutting machine using force sensing. A genetic algorithm (GA) based search is performed to select 3...
An inversion technique for estimating the structure parameters of layered media covered by a rough surface based on a genetic algorithm is proposed in this work. A theoretical model of scattering from three-dimensional arbitrary layered media with a 3D infinite rough surface based on the small perturbation method (SPM) is employed to calculate the forward scattering problem. The backscatting coefficients...
The dependable operation of brain-computer interfaces (BCI) based on electroencephalogram (EEG) signals requires precise classification of multi-channel EEG signals. The design of EEG interpretation and classifiers for BCI are open research questions whose difficulty stems from the need to extract complex spatial and temporal patterns from noisy multidimensional time series obtained from EEG measurements...
In this work, an evolutionary neural network (ENN) is proposed for forecasting net flow of a car sharing system. This work consists mainly of two contributions. The first is to develop a mixed optimization approach with genetic algorithm (GA) and back propagation (BP) training for the ENN. In particular, the crossover operator of the genetic algorithm is performed with multiple neural networks that...
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