Bayesian forecasting and dynamic models (2nd ed.)
Bayesian forecasting and dynamic models (2nd ed.)
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Based on the principle of Bayesian theory-based forecasting, a new forecasting model, called Bayesian Least Risk Forecasting model, is proposed in this paper. Firstly, the principle and modeling idea of Bayesian forecasting are illustrated with the explanation of the meaning of least risk forecasting. Then the advantages and learning algorithm of this model are discussed explicitly. In order to validate the prediction performance of Bayesian Least Risk Forecasting model, a simulated time series and practical data measured from some rotating machinery are used to compare the ability of prediction with classical artificial neural networks model. The results show that the bayesian model can contribute to a good accuracy of prediction.