期刊文献+

基于粗糙集的铁道车辆动力学设计参数重要度定量分析方法 被引量:1

Quantitative Analysis Method for Design Parameter Importance of Railway Vehicle Dynamics Based on Rough Set
下载PDF
导出
摘要 在建立车辆动力学仿真分析模型的基础上,确定设计参数的种类和数量;基于车辆的每类设计参数及其取值范围,采用拉丁超立方试验设计方法获取各类设计参数的数据样本;将数据样本的粗糙化描述为车辆动力学的知识表达系统;进而将粗糙集属性约简算法和互信息属性约简算法相结合,给出车辆动力学设计参数重要度的定量分析方法。以定量分析某型动车组悬挂参数重要度为例,验证了该方法的正确性和可行性。采用该方法有助于克服车辆设计参数众多带来的设计优化效率不高的问题。 On the basis of the establishment of vehicle dynamics simulation analysis model,the variety and quantity of the design parameters were determined.Based on each type of design parameters and their values range,the data samples of various types of design parameters were obtained by Latin hypercube experimental design method.The roughness of data sample was described as the knowledge representation system of vehicle dynamics.Then the attribute reduction algorithm of rough set and mutual information were combined to achieve the quantitative analysis method for the design parameter importance of vehicle dynamics.The quantitative analysis for the suspension parameter importance of a type of EMU was taken for example,the correctness and feasibility of the method was validated.This method contributes to overcome the low design and optimization efficiency caused by the numerous design parameters of vehicle.
出处 《中国铁道科学》 EI CAS CSCD 北大核心 2014年第3期90-96,共7页 China Railway Science
基金 国家自然科学基金资助项目(51305367) 国家"八六三"计划项目(2012AA112002)
关键词 车辆动力学 设计参数 重要度 粗糙集理论 互信息 定量分析 Vehicle dynamics Design parameter Importance Rough set theory Mutual information Quantitative analysis
  • 相关文献

参考文献9

  • 1SUAREZ B,FELEZ J,MAROTO J,et al.Sensitivity Analysis to Assess the Influence of the Inertial Properties of Railway Vehicle Bodies on the Vehicle's Dynamic Behavior [J].Vehicle System Dynamics,2013,51(2):251-279.
  • 2SUAREZ B,MERA J M,MARTINEZ M L,et al.Assessment of the Influence of the Elastic Properties of Rail Ve-hicle Suspensions on Safety,Ride Quality and Track Fatigue [J].Vehicle System Dynamics,2013,51(2):280-300.
  • 3王新锐.高速客车转向架悬挂参数灵敏度及耦合关系探讨[J].铁道机车车辆,2000,20(2):13-18. 被引量:5
  • 4PARK Chankyoung,KIM Youngguk,BAE Daesung.Sensitivity Analysis of Suspension Characteristics for Korean High Speed Train [J].Journal of Mechanical Science and Technology,2009,23(4):938-941.
  • 5PAWLAK Z.Rough Sets[J].International Journal of Computer-Information Sciences,1982,11(5):341-356.
  • 6刘新亮,郭波.适用于复杂系统仿真试验的试验设计方法[J].国防科技大学学报,2009,31(6):95-99. 被引量:6
  • 7瞿彬彬,卢炎生.基于粗糙集的属性约简算法研究[J].华中科技大学学报(自然科学版),2005,33(8):30-33. 被引量:33
  • 8LIU Dun,HU Pei,LI Tianrui,et al.An Approach for Attribute Weights Acquisition Based on Rough Sets Theory and Information Gain [C]//International Conference on Intelligent Systems and Knowledge Engineering.Paris:At-lantis Press,2007:1296-1302.
  • 9赵荣泳,张浩,李翠玲,樊留群,王骏.粗糙集连续属性离散化模型研究与应用要点分析[J].计算机工程与应用,2005,41(8):40-42. 被引量:15

二级参考文献26

  • 1Jin R C, Wei C, Agus S. An Efficient Algorithm for Constructing Optimal Design of Computer Experiments [J]. Journal of Statistical Planning and Inference, 2005, 134 (1): 268-287.
  • 2Owen A B. Orthogonal Arrays for Computer Experiments, Integration and Visualization [J]. Statistica Sinica, 1992, 2:439 - 452.
  • 3Morris M D, Mitchell T J. Exploratory Designs for Computational Experiments [J]. Journal of Statistical Planning and Inference, 1995, 43 (3): 381 - 402.
  • 4Ye K Q. Orthogonal Column Latin Hypercubes and Their Application in Computer Experiments [ J ]. Journal of the American Statistical Association--Theory and Method, 1998, 93 (444): 1430- 1439.
  • 5Fang K T, Ma C X, Winker P. Centered L2-discrepancy of Pandom Sampling and Latin Hypercube Design, and Construction of Uniform Designs [J]. Mathematics of Computation, 2002(71) : 275 - 296.
  • 6Tsumoto,Shusaku. Rough Set Methods and Applications[M].New York:Physica_Verlag, 2000.
  • 7Orlowska, Ewa. Incomplete Information: Rough Set Analysis[M].New York: Physica_Verlag, 1998.
  • 8Francis E H Taya,Lixiang Shen. Fault diagnosis based on Rough Set Theory[J].Engineering Applications of Artificial Iutelligence,2003;16:39-43.
  • 9F E H Tay,L Shen.Economic and ?nancial prediction using rough sets model[J].European Journal of Operational Research,2002; 141:641-659.
  • 10Slowinski R.RoughClassifica tion of HSV Patients. Intelligent Decision Support[M].Kluwer:Roman Slowinski, 1992:77-944.

共引文献55

同被引文献8

引证文献1

二级引证文献2

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