Name
Abstract | ||
|---|---|---|
A framework for modelling the safety of an engineering system using a fuzzy rule-based evidential reasoning (FURBER) approach has been recently proposed, where a fuzzy rule-base designed on the basis of a belief structure (called a belief rule base )f orms a basis in the inference mechanism of FURBER. However, it is difficult to accurately deter- mine the parameters of a fuzzy belief rule base (FBRB) entirely subjectively, in particular for complex systems. As such, there is a need to develop a supporting mechanism that can be used to train in a locally optimal way a FBRB initially built using expert knowledge. In this paper, the methods for self-tuning a FBRB for engineering system safety analysis are investigated on the basis of a previous study. The method consists of a number of single and multiple objective nonlinear optimization models. The above framework is applied to model the system safety of a marine engineering system and the case study is used to demonstrate how the methods can be implemented. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s10479-008-0327-0 | Annals OR |
Keywords | Field | DocType |
Safety analysis,Uncertainty,Fuzzy logic,Belief rule-base,Evidential reasoning,Optimization | System safety,Inference,Nonlinear programming,Belief structure,Fuzzy logic,Self-tuning,Artificial intelligence,Evidential reasoning approach,Machine learning,Mathematics,Fuzzy rule | Journal |
Volume | Issue | ISSN |
163 | 1 | 0254-5330 |
Citations | PageRank | References |
25 | 0.97 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Liu | 1 | 644 | 56.21 |
| Jian-Bo Yang | 2 | 3832 | 203.05 |
| Da Ruan | 3 | 2008 | 112.05 |
| Luis Martínez | 4 | 64 | 4.50 |
| Jin Wang | 5 | 317 | 13.43 |