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Particle swarm optimization (PSO) is an algorithm modelled on swarm intelligence that finds a solution to an optimization problem in a search space. In this paper, a PSO-based artificial neural network algorithm is proposed to automatically grading the learning results. Basically, the PSO algorithm is utilized to adjust the connection weights of the selected ANN topology. Taken mandarin learning as...
Introducing the rank-weight method into the basic ant colony optimization (ACO), we use the modified ACO to optimize the weights and thresholds value of neural networks (NN). And when the BPNN is being trained, this method can solve the disadvantages of running into the minimum easily, and enhance the convergence speed. So we get a heuristic method, which is good at time efficiency and derivation...
This paper proposes a new face recognition approach by using Independent Component Analysis (ICA) and Ensemble Classifiers based on Support Vector Machine (SVM). Firstly, to improve the quality of the face images, a series of image pre-processing techniques are used. Then the ICA based on Kernel Principal Component Analysis (KPCA) and FastICA is employed to extract features. At last, appropriate classifiers...
Nozzle plays very important role to control the gas flow during the interruption for SF6 circuit breaker (CB). Due to the higher non-linear global mapping relationship between interruption performance of SF6 CB and its nozzle structural parameters, artificial neural network (ANN) and genetic algorithm (GA) were applied to the nozzle parameter optimization of SF6 CB on the basis of the non-linear mapping...
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