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In speech recognition system, an improved multi-base neural network speech recognition model is proposed to solve the problem of long learning time and slow convergence rate of deep neural network. However, the improved model introduces a large number of parameters in the training process to make the model over-fitted in the test set, resulting in the deterioration of generalization ability and the...
Enterprise in financial trouble is a comprehensive event and the enterprise financial situation can be reflected through the liquidity ratio, earnings per share and net assets per share and cash content per share. Artificial neural network method is used to establish the financial early warning model to find the potential financial crisis at an early age. The experiment results show that BP neural...
The conventional algorithm of the BP neural network has some disadvantages such as in the vicinity of the target, if the learning factor is too small, the convergence may be too slow, and if the learning factor is too large, the convergence may be amended too much, leading to oscillations and even dispersing phenomenon. At the same time, the very slow speed of convergence and the main procedure is...
This paper proposes a new global optimization technique in which combines population migration algorithm (PMA) and radial basis function (RBF) neural networks learning algorithm for training RBF neural network. Compared with the traditional RBF training algorithm, the simulation results show that the method has a higher accuracy in a stringency and works well in avoiding sticking in local minima.
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