| Language | English |
|---|---|
| Pages | 569-585 |
| Journal | IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans |
| Volume | 37 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Jul 2007 |
Cite this
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Optimization Models for Training Belief-Rule-Based Systems. / Liu, J; Wang, J; Xu, D-L; Yang, J-B.
In: IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, Vol. 37, No. 4, 01.07.2007, p. 569-585.Research output: Contribution to journal › Article
TY - JOUR
T1 - Optimization Models for Training Belief-Rule-Based Systems
AU - Liu, J
AU - Wang, J
AU - Xu, D-L
AU - Yang, J-B
N1 - Other Details ------------------------------------ It is difficult to accurately determine rule-bases entirely subjectively, particularly for a large-scale rule-base. This paper presents optimisation models for a newly developed belief rule-base system. The models provide a non-black-box simulator for which input/output information can be incomplete or vague, either numerical or judgmental, or mixed. Application to analyse safety of engineering systems and leak detection in oil pipelines has shown their abilities to simulate real situations in a meaningful, efficient, consistent, and optimal way. The work relates to developments in two projects funded by EPSRC (GR/S85498/01) and DEFRA (AFM222) respectively, held in the University of Manchester.
PY - 2007/7/1
Y1 - 2007/7/1
U2 - 10.1109/TSMCA.2007.897606
DO - 10.1109/TSMCA.2007.897606
M3 - Article
VL - 37
SP - 569
EP - 585
JO - IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
T2 - IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
JF - IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
SN - 1083-4427
IS - 4
ER -