现代电子技术2017，Vol.40Issue(9)：148-151,4.DOI:10.16652/j.issn.1004-373x.2017.09.039
基于IPSO-SVR的水泥分解炉温度预测模型研究
Research on cement decomposing furnace temperature prediction model based on IPSO-SVR
摘要
Abstract
In order to establish a stable and reliable temperature prediction model for the decomposing furnace,in combina-tion with several main operating parameters closely related to the decomposing furnace temperature,a particle swarm optimiza-tion based support vector regression(PSO-SVR)machine algorithm is proposed. The thought of adaptive inertia weight is intro-duced into the particle swarm optimization algorithm to construct the decomposing furnace temperature prediction model. The model is compared with the unimproved one by means of simulation experiment. The experimental results show that the IPSO-SVR model has better forecasting ability,the correlation coefficient reached to 0.7075,the temperature prediction error abso-lute value is less than 7 ℃,and the error rate is within 0.8%.关键词
分解炉温度/粒子群算法/惯性权重/支持向量回归机/预测模型Key words
decomposing furnace temperature/particle swarm optimization algorithm/inertia weight/support vector regres-sion machine/prediction model分类
信息技术与安全科学引用本文复制引用
金星,徐婷,冷淼..基于IPSO-SVR的水泥分解炉温度预测模型研究[J].现代电子技术,2017,40(9):148-151,4.基金项目
吉林省科学技术厅计划项目(20150203003SF) （20150203003SF）
