{"refrec":{"BRefID":296143,"RR":"Liu, J.; Yang, J.-B.; Ruan, D.; Martinez, L.; Wang, J. (2008). Self-tuning of fuzzy belief rule bases for engineering system safety analysis. Annals of Operations Research 163(1): 143-168. https://dx.doi.org/10.1007/s10479-008-0327-0","BEntID":288232,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":1,"RefStringPartII":". Annals of Operations Research 163(1): 143-168. https://dx.doi.org/10.1007/s10479-008-0327-0","DocTypID":8,"DocType":"Journal article","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Liu, J.; Yang, J.-B.; Ruan, D.; Martinez, L.; Wang, J.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Liu, J. et al.","Englishabstract":"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) forms a basis in the inference mechanism of FURBER. However, it is difficult to accurately determine 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.","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"Self-tuning of fuzzy belief rule bases for engineering system safety analysis","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2024-12-10 01:33:17.368041","timezone_type":1,"timezone":"+01:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":"safety analysis; uncertainty; fuzzy logic; belief rule-base; evidentialreasoning; optimization","OtherDescriptors":null,"Notes":null,"AnaPub":2008,"MonPub":null,"DateUpdate":"2022-05-03","DateCreate":"2018-05-15","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":"WOS:000258190600008","VABBcode":null,"OpenAcc":0,"DOI":"10.1007/s10479-008-0327-0"},"refs":null,"anarec":{"AnaID":296143,"PubliDate":2008,"Pagination":"143-168","XtraPublOfAnaID":null,"ISBN":null,"Volume":"163","Issue":"1","BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":263432,"SerRR":"Annals of Operations Research. 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