首页|期刊导航|高技术通讯（英文版）|Prediction model for permeability index by integrating case-based reasoning with adaptive particle swarm optimization
高技术通讯（英文版）2009，Vol.15Issue(3)：267-271,5.DOI:10.3772/j.issn.1006-6748.2009.03.008
Prediction model for permeability index by integrating case-based reasoning with adaptive particle swarm optimization
Prediction model for permeability index by integrating case-based reasoning with adaptive particle swarm optimization
摘要
Abstract
To effectively predict the permeability index of smelting process in the imperial smelting furnace, an intelligent prediction model is proposed. It integrates the case-based reasoning (CBR) with adaptive particle swarm optimization (PSO). The number of nearest neighbors and the weighted features vector are optimized online using the adaptive PSO to improve the prediction accuracy of CBR. The adaptive inertia weight and mutation operation are used to overcome the premature convergence of the PSO. The proposed method is validated a compared with the basic weighted CBR. The results show that the proposed model has higher prediction accuracy and better performance than the basic CBR model.关键词
lead and zinc smelting/ permeability index prediction/ case-based reasoning (CBR)/ adaptive particle swarm optimization (PSO)Key words
lead and zinc smelting/ permeability index prediction/ case-based reasoning (CBR)/ adaptive particle swarm optimization (PSO)分类
信息技术与安全科学引用本文复制引用
Zhu Hongqiu ,Yang Chunhua,Gui Weihua..Prediction model for permeability index by integrating case-based reasoning with adaptive particle swarm optimization[J].高技术通讯（英文版）,2009,15(3):267-271,5.基金项目
Supported the by the National Natural Science Foundation (No. 60874069, 60634020), the National High Technology Research and Development Programme of China (No. 2009AA04Z124), and Hunan Provincial Natural Science Foundation of China (No. 09JJ3122). （No. 60874069, 60634020）
