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The influence of blasting vibration to surroundings around the blasting area can not be ignored, in order to guarantee the safety of surroundings around blasting area, blasting vibration forecasting model based on neural network is established by improved BP neural network in this paper. The inputs of the model are the largest single fire dynamite, height difference and horizontal distance between...
In the study, back-propagation neural networks (BP-NN) theory and genetic algorithm (GA) were used to build a nonlinear prediction model reflecting the relationship between technics parameters of electric field aging and mechanical properties of LY12 aluminum alloy. In this model, electric field intensity, aging temperature and time were as input parameters. Tensile strength, yield strength and micro-yield...
Chaos and artificial neural networks have been providing a new rout for investigating the complicated nonlinear time series. As the traditional neural networks are easy to get slow convergence and produce large redundancy which might consequently bring low efficiency, the biased wavelet neural networks is employed to build chaotic time series forecasting. Efforts are also made to assess the forecast...
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