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In this paper, based on investigating and analyzing on the affecting factors for support type of development roadways as well as the successful support cases in Chengchao Iron mine, the improved BP neural network is put forward to study on the support type of development roadways. It may be seen from the learning course of learning samples and the prediction results of support types that whether the...
This paper presents a new method of the Emotion Recognition Model using the BP Neural Network, in order that E-Learning system simulates the real teaching situation better. As result of the experiment, the model shows a high rate of recognition and better real-time performance.
Neural network has been widely used for nonlinear mapping, time-series estimation and classification. The backpropagation algorithm is a landmark of network weights training. Although the vast weights update algorithms have been developed, they are often plagued by convergence to poor local optima and low learn velocity. The unscented Kalman filter is a nonlinear parameter estimation algorithm. By...
In this paper, the principle of neural network blind equalization algorithm was depicted, the fault of traditional BP (back propagation) algorithm, which is slow convergence rate and easy to fall into a local minimum, was analyzed, the influence of momentum factor to equalization performance was researched, the convergence track of traditional BP algorithm and momentum factor BP algorithm was compared...
Abrasive water jet can be applied to perforate the oil formation rock. The perforation depth generated by abrasive water jet is nonlinearly influenced by so many factors that it is difficult to mathematically correlate the perforation depth with influencing factors. So the back propagation (BP) neural network is introduced to establish the model for predicting perforation depth generated by abrasive...
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