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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...
In indoor environment, there are gross errors in random measured values of base station, which has effect on generalization ability of BP neural network and then results in low location accuracy. In order to improve location accuracy, location algorithm of BP Neural Network based on residual analysis is proposed, namely conducting pretreatment on measured values separately in training phase and location...
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...
Deformation that happens in the real world is a nonlinear process, and so are the outliers in deformation observations. With the requirements on automation, real-time and accuracy becoming stronger and stronger, it is also more and more important to fast detect and remove the outliers in monitoring observations. In the paper the approximation of nonlinear function mapping relation using artificial...
Putting forward a face recognition method based on Diagonal Principal Component Analysis and BP neural network. Firstly, do the dimension reduction to the sample data and take the DiaPCA method to avoid the information drop; Then, use the classics BP neural network to do the face detection. It not only shorten the net training time, but also improve the accuracy of the recognition. It used 1000 face...
To convert GPS height by Artificial Neural Networks, there are still many problems which need further research. In this paper we conduct more in-depth analysis and study more about the specific problems such as the determination of hidden layer, the determination of hidden layer nodes, network training times, selections of learning rate and initial weight values and so on. After the improved setting...
Agricultural products information on the Internet is constructed repeatedly, the content is haphazard and sharing resources can not be used, then a classification of improved neural network which is based on the adjustment and optimization of the weight is presented. The adjustment of weight, optimization of network structure and reasonable adjustment of parameters of BP neural network are discussed,...
BP neutral network and its improved algorithms are applied to compensate sensor's performance. The defects of BP, for example, converging slowly, being easy to converge to minimum of one part are improved efficiently. Training programs are done. Results show that the performance of sensor is improved highly. Network has a high converging speed and good precision. The correction precision increases...
The paper is given a new modified differential evolution (MDE) algorithm in which a novel mutation operator is introduced. The MDE algorithm can obtain a good balance between global search and local search and was applied in BP neural network training. The numerical results demonstrate that the new MDE algorithm has the abilities of good global search and faster convergence speed and higher convergence...
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