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In this study, a deep denoising recurrent temporal restricted Boltzmann machine network is proposed for long-term prediction of time series. The network is a deep dynamic network model which is stacked by multiple denoising recurrent temporal restricted Boltzmann machines with strong modeling ability for complex high noise time series data. To better deal with high noise data, a random noise is added...
In this paper, the best irradiation technology for improving the quality of liquor by 60Co-γ irradiation was studied. Different doses of rays on liquor quality Law model was built by Bayesian regularization BP neural network method. This model was used for prediction and verification, and then the particle swarm optimization algorithm was used to predict the process parameters of the irradiation process...
Corporation financial distress has been an important issue for study in the financial fields. This paper uses traditional BP neural network model and proposes PNN model to predicate financial distress. The sample consists of 276 companies listed on the Shanghai Stock Exchange and Shenzhen Stock Exchange over the period 2001–2010. Factor analysis is used to lower correlation and reduce dimensionality...
Aiming at the problems of the wear condition monitoring, grey theory and auto-regressive combination forecasting model was put forward, and the combination model was build. The rough trend of the wear particle content change can be reflected through grey theory, and the detail of the change can be reflected through auto-regressive model. By testing and comparing a set of Ferro graphic data, the result...
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