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Artificial To better achieve character recognition, analyze the impact of noise character. BP neural network application describes the process of character recognition, and the corresponding algorithm improvements. Created with MATLAB and training the neural network to identify the different samples, combined toolbox simulink simulation module, so that the character recognition to get better recognition...
Data pre-processing in modeling of neural network (NN) is relatively more complicated and usually manual. Trial and error method is commonly used to determine the number of hidden layer neurons, which is easily affected by human factors and is opportunistic. Relevant training parameters using default value commonly result in lower model accuracy. In this paper, a NN load forecasting model with higher...
Duncan E-B model has been widely used in engineering practice. And how to determine the parameters of the model accurately and easily is the main step to ensure the reliability of the results. Based on BP neural network in MATLAB toolbox, this paper aim to establish the non-linear relation between the density γ, porosity e and the constitutive model parameter K (Kb, Rf, Q0) which is difficult to be...
Radial basis function (RBF) neural network is used to predict the blast furnace hot metal based on its characteristics such as fast convergence and global optimization. As hot metal silicon content had close relationship with furnace temperature, the change of temperature in furnace was reflected indirectly by hot metal silicon content. Newrbe function in Matlab was applied for function approximation...
Models of transformer fault diagnosis were developed by using on-line data to improve the conventional testing method and physical law methods. The operation data of 7 variables that affect transformer fault had been studied by using principal component analysis method, 5 principal components had been obtained and the contributions of the principal components had been computed. Based on the factors,...
The MAV accurate modes are typically unavailable. Most traditional methods for system design are complex and can not get satisfactory effect. Recent work in dynamic inversion with neural network may be applied to control a MAV where the reference commands include position, velocity, attitude and angular rate. This control technology can provide the MAV with an admirably command follow and steady control...
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