Possibility and evidence theory based design optimization: A survey

doi:10.1109/FSKD.2010.5569678

	Possibility and evidence theory based design optimization: A survey
	Liang, Haofeng
	2010
会议录名称	Proceedings - 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010
卷号	1
页码	264-268
出版者	IEEE Computer Society
摘要	An annotated survey of approaches to design optimization based on possibility theory and evidence theory is presented and prominent characteristics are described in this paper, especially addressing epistemic uncertainty for large-scale and complex systems when statistical data is scarce or incomplete. We first analyze the uncertainties encountered in design and the limitations of probabilistic approach. Then possibility-based design optimization (PBDO), evidence-based design optimization (EBDO) and their integrated approaches are comparatively investigated respectively, form the viewpoints of computational development and performance improvement. After that, this paper discusses the fusion technologies and an example of integrated approach in reliability to reveal the qualitative value and efficiency. In the end, technical difficulties, application areas and future directions are summarized. ©2010 IEEE.
关键词	Integrated control Reviews Surveys Uncertainty analysis Computational development Design optimization Epistemic uncertainties Evidence theories Large-scale and complex systems Possibility theory Possibility-based design optimizations Probabilistic approaches
DOI	10.1109/FSKD.2010.5569678
收录类别	EI
语种	英语
EI入藏号	20104813422374
EI主题词	Computation theory
来源库	Compendex
分类代码	721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 731.1 Control Systems - 903.2 Information Dissemination - 922.1 Probability Theory
引用统计	无
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/116163
专题	兰州理工大学
作者单位	School of Mechatronics Engineering, Lanzhou University of Technology, Lanzhou, China
第一作者单位	兰州理工大学
推荐引用方式 GB/T 7714	Liang, Haofeng. Possibility and evidence theory based design optimization: A survey[C]:IEEE Computer Society,2010:264-268.