期刊文献+

基于LSSVM-MODE的水煤浆优化配煤研究 被引量:4

Research on Optimization Coal Blending of Coal Water Mixture Based on LSSVM-MODE
下载PDF
导出
摘要 根据茂名洁能水煤浆厂常用的三种配煤方式,利用最小二乘支持向量机(LSSVM)对球磨机电流和水煤浆浓度进行多目标建模,并采用基于Pareto最优概念的多目标微分进化(MODE)算法,对运行工况进行寻优,然后根据模糊集理论在Pareto解集中求得满意解,获得了水煤浆浓度高、生产成本低的三种配煤优化调整策略,并得出了最佳配煤方案,从而确定了水煤浆生产优化配煤策略。 according to the three kinds coal blending methods frequently used in Maoming CWM plant,the LSSVM(Least Square Support Vector Machines) was proposed to construct multi-objective optimization model for CWM concentration and ball mill electric current.MODE(multi-objective differential evolution) based on Pareto optimal concept is used to perform a search for determining the optimum solutions,from which three kinds optimum adjustments that could increase concentration and lower production cost of CWM is obtained based on fuzzy theory.Then thebest coal blending project is acquired that could optimize preparation of coal water mixture.
出处 《选煤技术》 CAS 北大核心 2008年第3期16-20,共5页 Coal Preparation Technology
关键词 水煤浆 优化配煤 最小二乘支持向量机 多目标微分进化算法 coal water mixture optimized coal blending least square support vector machines multi-objective differential evolution
  • 相关文献

参考文献7

  • 1尉迟唯,李保庆,李文,陈皓侃,王志忠.煤的岩相显微组分对水煤浆性质的影响[J].燃料化学学报,2003,31(5):415-419. 被引量:26
  • 2D G Mayer, B P Kinghorn, A A Archer. Differential evolution- An easy and efficient evolutionary algorithm for model optimization [ J ] . Agriculttural Systems, 2005, 83 (3): 315-328.
  • 3F Xue, A C Sanderson, R J Graves. Pareto - based multi - objective differential evolution [ C ] . In: Proc of the 2003 Congress on Evolutionary Computation(CEC'2003) . Piseataway, N J: IEEE Press, 2003. 862 - 869.
  • 4T Robe, B Filipe. DEMO: Differential evolution for multiobjeetive optimization [ C ] . The 3rd Intl Conf on Evolutionary Multi - Criterion Optimization (EMO 2005) . Guanajuato, Mexico, 2005.
  • 5V L Huang, P N Suganthan, A K Qin, et al. Multiobjective Differential Evolution with External Archive and Harmonic Distance - Based Diversity Measure [ R ] .Nanyang Technological University, 2005.
  • 6张利彪,周春光,马铭,孙彩堂.基于极大极小距离密度的多目标微分进化算法[J].计算机研究与发展,2007,44(1):177-184. 被引量:29
  • 7Harry C S, Rughooputh , Robert T F Ah King. Environ mental/Economic Dispatch of Thermal Units using an Elitist Multiobjective Evolutionary Algorithm [ C] . 2003 IEEE International Conference on Volume 1,2003.48 - 53.

二级参考文献22

  • 1雷德明,吴智铭.基于个体密集距离的多目标进化算法[J].计算机学报,2005,28(8):1320-1326. 被引量:23
  • 2吴家珊 宋永玮.煤的性质对水煤浆特性的影响[J].燃料化学学报,1987,15(4):298-299.
  • 3周安宁 王祖侗 陈邦杰.神木煤显微组分的表面特性[J].燃料化学学报,1989,17(4):381-384.
  • 4ZHANG Rong-zeng, ZENG Fang, HU Kun-Mu. Research on CWM preparation technique with Chinese coals[ A]. Proceedings of 6th International Symposium on Coal Slurry Combustion and Technology[C]. Orlando, Florida, USA, 1984,234-250.
  • 5Shin-ichi Watanabe, Ken-ichi Katabe. Effect of several factors on HCWS theological property[ A]. Proceedings of 6th International Symposium on Coal Slurry Combustion and Technology[C]. Orlando. Florida. USA. 1984.467-478.
  • 6Funk E. Coal-watershary and methods for its preparation[P]. US Patent, 4 282 006.
  • 7J D Schaffer.Multiple objective optimization with vector evaluated genetic algorithms[C].In:John J Grefenstette ed.Proc of the 1st Int'l Conf on Genetic Algorithms.Mahwah:Lawrence Erlbaum Associates,Inc,1985.93-100
  • 8J Horn,N Nafpliotis,D E Goldberg.A niched Pareto genetic algorithm for multiobjective optimization[C].In:Proc of the 1st IEEE Conf on Evolutionary Computation.Piscataway:IEEE Service Center,1994.82-87
  • 9E Zitzler,L Thiele.Multiobjective evolutionary algorithms:A comparative case study and the strength Pareto approach[J].IEEE Trans on Evolutionary Computation,1999,3(4):257 -271
  • 10N Srinivas,K Deb.Multiobjective optimization using non-dominated sorting in genetic algorithms[J].Evolutionary Computation,1994,2(3):221-248

共引文献53

同被引文献81

引证文献4

二级引证文献21

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部