| 000 | 01046camuu22003014a 4500 | |
| 001 | 000045427550 | |
| 005 | 20080319143404 | |
| 008 | 051214s2006 flua b 001 0 eng | |
| 010 | ▼a 2005056046 | |
| 020 | ▼a 1584886447 (acid-free paper) | |
| 020 | ▼a 9781584886440 | |
| 035 | ▼a (KERIS)REF000012427313 | |
| 040 | ▼a DLC ▼c DLC ▼d YDX ▼d BAKER ▼d TWU ▼d DLC ▼d 211009 | |
| 042 | ▼a pcc | |
| 050 | 0 0 | ▼a TA330 ▼b .A995 2006 |
| 082 | 0 0 | ▼a 620.001/51 ▼2 22 |
| 090 | ▼a 620.00151 ▼b A989u | |
| 100 | 1 | ▼a Ayyub, Bilal M. |
| 245 | 1 0 | ▼a Uncertainty modeling and analysis in engineering and the sciences / ▼c Bilal M. Ayyub, George J. Klir. |
| 260 | ▼a Boca Raton, FL : ▼b Chapman & Hall/CRC , ▼c 2006. | |
| 300 | ▼a 378 p. : ▼b ill. ; ▼c 25 cm. | |
| 504 | ▼a Includes bibliographical references (p. 353-368) and index. | |
| 650 | 0 | ▼a Engineering mathematics. |
| 650 | 0 | ▼a Uncertainty ▼x Mathematical models. |
| 650 | 0 | ▼a Reliability (Engineering) |
| 700 | 1 | ▼a Klir, George J. , ▼d 1932- |
| 945 | ▼a KINS |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 620.00151 A989u | 등록번호 121167099 | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
목차
Systems, Knowledge, and Ignorance
Data Abundance and Uncertainty
Systems Framework
Knowledge
Ignorance
From Data to Knowledge for Decision Making
Encoding Data and Expressing Information
Introduction
Identification and Classification of Theories
Crisp Sets and Operations
Fuzzy Sets and Operations
Generalized Measures
Rough Sets and Operations
Gray Systems and Operations
Uncertainty and Information Synthesis
Synthesis for a Goal
Knowledge, Systems, Uncertainty, and Information
Measure Theory and Classical Measures
Monotone Measures and Their Classification
Dempster-Shafer Evidence Theory
Possibility Theory
Probability Theory
Imprecise Probabilities
Fuzzy Measures and Fuzzy Integrals
Uncertainty Measures
Introduction
Uncertainty Measures: Definition and Types
Nonspecificity Measures
Entropy-Like Measures
Fuzziness Measure
Application: Combining Expert Opinions
Uncertainty-Based Principles and Knowledge Construction
Introduction
Construction of Knowledge
Minimum Uncertainty Principle
Maximum Uncertainty Principle
Uncertainty Invariance Principle
Methods for Open-World Analysis
Uncertainty Propagation for Systems
Introduction
Fundamental Methods for Propagating Uncertainty
Propagation of Mixed Uncertainty Types
Expert Opinions and Elicitation Methods
Introduction
Terminology
Classification of Issues, Study Levels, Experts, and Process Outcomes
Process Definition
Need Identification for Expert Opinion Elicitation
Selection of Study Level and Study Leader
Selection of Peer Reviewers and Experts
Identification, Selection, and Development of Technical Issues
Elicitation of Opinions
Documentation and Communication
Visualization of Uncertainty
Introduction
Visualization Methods
Criteria and Metrics for Assessing Visualization Methods
Intelligent Agents for Icon Selection, Display, and Updating
Ignorance Markup Language
Appendix A: Historical Perspectives on Knowledge
정보제공 :
