Application of Bayesian Neural Networks in Steam Pipe Network Prediction
MA Yong1,2，SUN Yanguang1
（1. Automation Research and Design Institute of Metallurgical Industry, Beijing 100071, China 2. Shanghai Aritime Information Technology Co., Ltd., Shanghai 201900, China）
Abstract：Steam pipe network is typical nonlinear network structure. It is instructive to increase predictive capacity to steam pipe network highly effective. Bayesian neural networks is well generalization and better calculate capability. A penalty term which could be interpreted as an indication of the complexity of the network was introduced into the objective function to present the occurrence of “overfitting”. Compared with the conventional BP neural network, it has the advantages of faster convergence rate, higher stability and ability for generalization. The result had certain guided signification to accelerate the construction of hybrid process energysaving and emissionreduction.
2014, Vol. 24 
