Name
Title | ||
|---|---|---|
Robust Methodology for Characterizing System Response to Damage: Approach Based on Partial Order |
Abstract | ||
|---|---|---|
To describe the response of engineering complex systems to various damage mechanics, engineers have traditionally use number-valued utilities to describe the results of different possible outcomes, and (number-valued) probabilities (often, subjective probabilities) to describe the relative frequency of different outcomes. This description is based on the assumption that experts can always make a definite preference between two possible outcomes, i.e., that the set of all outcomes is linearly (totally) ordered. In practice, experts often cannot make a choice, their preference is only a partial order. In this paper, we describe a new approach based on partial order. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-24588-9_31 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
partial order | Complex system,Preference relation,Mathematical optimization,Systems theory,Linear space,Frequency,Artificial intelligence,Damage mechanics,Mathematics,Partially ordered set | Conference |
Volume | ISSN | Citations |
2907 | 0302-9743 | 3 |
PageRank | References | Authors |
0.59 | 2 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul J. Tanenbaum | 1 | 74 | 8.11 |
| Carlos De La Mora | 2 | 3 | 0.59 |
| Piotr Wojciechowski | 3 | 24 | 4.75 |
| Olga Kosheleva | 4 | 97 | 54.24 |
| Vladik Kreinovich | 5 | 1091 | 281.07 |
| Scott A. Starks | 6 | 61 | 12.76 |
| Alexandr V. Kuzminykh | 7 | 3 | 0.59 |