节点文献
混合神经网络模型用于煤焦气化过程的模拟
Application of Hybrid Neural Network Models for Simulation of Coal Char Gasification Process
【摘要】 以煤焦气化反应模型为基础,结合BP神经网络参数估计器,建立了用于模拟煤焦气化过程的混合神经网络模型。结果表明该混合神经网络模型能很好地描述煤焦的气化过程,可以得到在实验过程中无法测得的2个参数,即:在煤焦中具有活性的碳与总碳的比值A和具有活性碳的单位质量反应速率Rr。
【Abstract】 Based on the gasification reaction model of coal chars,the hybrid neural network model for simulation of coal char gasification process was set up,connecting with BP neural network parameter estimator.The results show that the hybrid neural network model is quite feasible to describe the gasification process of coal chars and the two parameters(A,the ratio of the carbon with activity and the total carbon in coal char;R_r,the unit mass reaction rate of the carbon with activity in coal char),which can not be measured directly in experiments.
【关键词】 混合神经网络模型;
煤焦;
气化过程;
模拟;
【Key words】 hybrid neural network model; coal char; gasification process; simulation;
【Key words】 hybrid neural network model; coal char; gasification process; simulation;
【基金】 国家重点基础研究发展规划(973计划)(2004CB217704)
- 【文献出处】 华东理工大学学报(自然科学版) ,Journal of East China University of Science and Technology(Natural Science Edition) , 编辑部邮箱 ,2009年02期
- 【分类号】X832
- 【被引频次】6
- 【下载频次】162