本文已被：浏览 1547次 下载 3525次
Received:January 22, 2011 Revised:March 04, 2011
Received:January 22, 2011 Revised:March 04, 2011
中文摘要: 针对氧化铝回转窑烧结过程中存在的多变量、强耦合、非线性、环境恶劣、煤粉和料浆成分不稳定等因素造成的烧结带温度不稳定,熟料质量低等难题,提出一种基于朴素贝叶斯分类(NBC)算法的回转窑烧结温度预测模型.采用FastICA 算法,找到回转窑热工数据的独立成分,从而满足NBC 的属性之间相互独立的条件,并通过AdaBoost 算法对模型进行提升.实验结果表明,这种模型具有较好的控制效果.
Abstract:The sintering temperature in rotary kiln is usually hard to be stable because of complex industrial environment. In this paper, we present a prediction model based on Bayesian classification algorithm to predict the trend of the amount of feed coal for controlling the sintering temperature in rotary kiln. To avoid the influence of attribute independence assumption of Bayesian classification algorithm, the FastICA algorithm used to find the independent components of the working condition data set in rotary kiln. Then we use AdaBoost algorithm to find a best classifier. The final simulation results show that the model has better control performance.
keywords: naive bayes prediction model rotary kiln ICA AdaBoost
文章编号： 中图分类号： 文献标志码：
基金项目:国家自然科学基金(60874096,50704016)
引用文本：
丁钢坚,张小刚.贝叶斯分类算法应用于回转窑烧结温度预测模型.计算机系统应用,2011,20(9):200-203
DING Gang-Jian,ZHANG Xiao-Gang.Prediction Model of Bayesian Classification Algorithm Applied to Control Sintering Temperature in Rotary Kiln.COMPUTER SYSTEMS APPLICATIONS,2011,20(9):200-203
丁钢坚,张小刚.贝叶斯分类算法应用于回转窑烧结温度预测模型.计算机系统应用,2011,20(9):200-203
DING Gang-Jian,ZHANG Xiao-Gang.Prediction Model of Bayesian Classification Algorithm Applied to Control Sintering Temperature in Rotary Kiln.COMPUTER SYSTEMS APPLICATIONS,2011,20(9):200-203
