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A large percentage of the cost of rework can be avoided by finding more faults earlier in a software testing process. Therefore, determination of which software testing phases to focus improvements work on, has considerable industrial interest. This paper evaluates the use of five different techniques, namely particle swarm optimization based artificial neural networks (PSO-ANN), artificial immune...
Gaussian Process Regression (GPR) as a new kernel machine learning technique holds many advantages such as programming easily, self-adaptive acquisition of hyper-parameters and prediction with probability interpretation. Presently, the hyper-parameters of GPR are got by maximizing likelihood function of training samples based on conjugate gradient algorithm. However, the algorithm has the shortcomings...
Short term load forecasting is essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of power system. artificial neural networks are employed for short term load forecasting owing to their powerful non-linear mapping capabilities. These are generally trained through backpropagation, genetic algorithm (GA), particle swarm optimization (PSO) and...
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