期刊文献+

证据推理的近似计算研究 被引量:4

Research on the approximation algorithm of the evidential thoeory
在线阅读 下载PDF
导出
摘要 在Dempster-Shafer证据推理中,计算复杂度是它应用面临的主要问题之一,主要方法是减少焦元的数目.通过对置信函数近似的定性和定量分析论证,提出了最优近似算法,并利用遗传算法进行近似计算,给出多步近似和一步近似两个快速算法.仿真表明,两者较其他算法有明显的改进. In the Dempster-Shafer theory,the computational complexity is one of the main points of criticism this theory has to face.To solve this problem,many approximation algorithms,which always reduce the focal elements,are proposed.In this paper,a simple optimal approximation is proposed by analyzing its reasonability in quality and quantity.The genetic algorithm is applied for approximation for the first time.Then two fast algorithms,one step approximation and multi-step approximation,are proposed.As a conclusion of simulation these algorithms are better than other algorithms in accuracy and computation burden.
出处 《西安电子科技大学学报》 EI CAS CSCD 北大核心 2011年第2期187-193,共7页 Journal of Xidian University
基金 国家自然科学基金重点资助项目(60634030) 国家自然科学基金资助项目(60702066 60802075) 教育部新世纪优秀人才资助项目(NCET-06-0878) 航空科学基金资助项目(20090853013) 陕西省自然科学基础研究计划资助项目(2010JQ8032) 西北工业大学科技创新基金资助项目(2008KJ02025)
关键词 DEMPSTER-SHAFER理论 证据推理 近似算法 遗传算法 信息融合 Dempster-Shafer theory evidential theory approximation algorithm genetic algorithm data fusion
  • 相关文献

参考文献11

  • 1Yao Y Y, Lingras P J. Interpretations of Belief Functions in the Theory of Rough Sets[ J]. Information Sciences, 1998, 104 ( 1- 2) : 81-106.
  • 2刘大有,李岳峰.广义证据理论的解释[J].计算机学报,1997,20(2):158-164. 被引量:18
  • 3戴冠中,潘泉,张山鹰,张洪才.证据推理的进展及存在问题[J].控制理论与应用,1999,16(4):465-469. 被引量:65
  • 4Voorbsaak F. A Computationally Efficient Approximation of Dempster-Shafer Theory[J]. Int J Man-machine Studies, 1989, 30 (2) : 525-536.
  • 5Tessem B. Approximation for Efficient Computation the Theory of Evidence[ J]. Artificial Intelligence, 1993, 61(2) : 315-329.
  • 6Lowrance J D, Garvey T D, Strat T M. A Framework for Evidential-reasoning Systems[ C] //Proceedings of the 5th National Conference of American Association for Artificial Intelligence: Vol 2. Philadelphia: AAAI Press, 1986: 896-903.
  • 7Bauer M. Approximation Algorithms and Decision Making in the Dempster-Shafer Theory of Evidemce--an Empirical Study[ J]. Int J Approximation Reasoning, 1997, 17(2-3) : 217-237.
  • 8Dubois D, Prude H. Consonant Approximation of Belief Function[ J]. Int J Approx Reasoning 1990, 22(4) : 418-449.
  • 9Harmanec D. Faithful Approximation of Belief Function[ J]. Uncertainty in Artificial Intelligence, 2009, 16(3) : 63-77.
  • 10Munakata T. Fundamentals of the New Artificial Intelligence: Beyond Traditional Paradigms[ M]. Princeton: Spring-Verlag, 2008: 195-245.

二级参考文献28

共引文献81

同被引文献37

  • 1李新德,杨伟东,Jean Dezert.一种快速分层递阶DSmT近似推理融合方法(C)[J].华中科技大学学报(自然科学版),2011,39(S2):150-152. 被引量:4
  • 2苏子健,钟毅芳.系统近似建模技术的研究与比较[J].系统工程与电子技术,2005,27(5):834-836. 被引量:10
  • 3刘大有,李岳峰.广义证据理论的解释[J].计算机学报,1997,20(2):158-164. 被引量:18
  • 4韩崇昭,朱洪艳,段战胜,等.多源信息融合[M].2版.北京:清华大学出版社,2010.
  • 5Ghosh D, Dube T, Shivaprasad A P. Script Recognition-A Review [J] : IEEE Trans on Pattern Analysis and Machine Intelligence, 2010, 32(12): 2142-2161.
  • 6Margner V, Abed H E. ICDAR 2011-Arabic Handwriting Recognition Competition [C]//Proc of the 2011 llth International Conference on Document Analysis and Recognition (ICDAR). Beijing: IEEE, 2011: 1444-1448.
  • 7Kherallah M, Bouri F, Alimi A M. On-line Arabic Handwriting Recognition System Based on Visual Encoding and Genetic Algorithm [J]. Engineering Applications of Artificial Intelligence, 2009, 22(1): 153-170.
  • 8A1-Muhtaseb H A, Mahmoud S A, Qahwaji R S. Recogntion of Off-line Printed Arabic Text Using Hidden Markov Models [J]. Signal Processing, 2008, 88(12) : 2902-2912.
  • 9A1-Jamimi H A, Mahmoud S A. Arabic Character Recognition Using Gabor Filters [J/OL]. [2010-03-10]. http:// china, springerlink, com/content/w6040hx428389w68/fulltext, pdf.
  • 10A1-Emami S, Usher M. On-Line Recognition of Handwritten Arabic Characters [J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 1990, 12(7) : 704-710.

引证文献4

二级引证文献5

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