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Aiming at the complexity of interior and variety of exterior structure of stock price system, this paper analyzes principles of stock prediction based on BP neural network, provides prediction model for stock market by utilizing three-layered feed forward neural networks, presents topology of network, principles of determining the number of hidden layers, selection and pretreatment of sample data...
An approach for software flexibility measurement and measurement indexes based on BP neural network were proposed. By using the self-organizing, self-learning and self- adapting properties of BP neural networks, the rule of software flexibility measurement indexes weight concealed in the training data could be learned by means of BP neural networks automatically adjust indexes weight of measurement...
A method based on the neural network to predict the strains of the gas generator in a liquid rocket engine is presented for the fault analysis of the gas generator. A modified back-propagation algorithm is proposed to train the neural network. The training and testing samples are generated with an experiment. In the experiment, four strains in the risk domain of the gas generator and three forced...
An online identification approach for boundary condition identification of fluid-filled piping systems is developed. Considering the lateral vibration of the fluid-filled pipes, the method combines the traveling wave method and the BP (backpropagation) neural network to estimate the boundary parameters. The traveling wave method is used to generate the training samples that contain several lower natural...
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