The influence of sulfur content in raw materials on oxidized pellets was studied. The results show that most sulfur exists in the form of elementary sulfur in pyrite cinder, and over 95% sulfur is removed in producing...The influence of sulfur content in raw materials on oxidized pellets was studied. The results show that most sulfur exists in the form of elementary sulfur in pyrite cinder, and over 95% sulfur is removed in producing pyrite cinder oxidized pellets. The compressive strength of fired pellets drops from 3 186 N to 2 405 N when the ratio of pyrite cinder increases from 40% to 70% under the conditions of preheating at 900℃ for 9 min and firing at 1 230 ℃ for 15 min. The porosity and microstructures of fired pellets prove that the higher ratio of pyrite cinder is given, and the more holes and cracks are achieved, leading to the better reducibility index （RI） and reduction swelling index （RSI）, and the lower compressive strength of fired pellets and the worse reduction degradation index （RDI）.展开更多
A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems....A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.展开更多
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 par- ticle ...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 par- ticle swarm optimization （PSO）. The nmnber 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.展开更多
基金Project(2007k02) supported by the Technology Fund of the Land and Resources Department of Hunan Province, China
文摘The influence of sulfur content in raw materials on oxidized pellets was studied. The results show that most sulfur exists in the form of elementary sulfur in pyrite cinder, and over 95% sulfur is removed in producing pyrite cinder oxidized pellets. The compressive strength of fired pellets drops from 3 186 N to 2 405 N when the ratio of pyrite cinder increases from 40% to 70% under the conditions of preheating at 900℃ for 9 min and firing at 1 230 ℃ for 15 min. The porosity and microstructures of fired pellets prove that the higher ratio of pyrite cinder is given, and the more holes and cracks are achieved, leading to the better reducibility index （RI） and reduction swelling index （RSI）, and the lower compressive strength of fired pellets and the worse reduction degradation index （RDI）.
基金Projects(50275150,61173052) supported by the National Natural Science Foundation of ChinaProject(14FJ3112) supported by the Planned Science and Technology of Hunan Province,ChinaProject(14B033) supported by Scientific Research Fund Education Department of Hunan Province,China
文摘A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.
基金supported by the by the National Natural Science Foundation(No.60874069,60634020)the National High Technology Research and Development Programme of China(No.2009AA04Z124)Hunan Provincial Natural Science Foundation of China(No.09JJ3122)
文摘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 par- ticle swarm optimization （PSO）. The nmnber 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.
