Constrained abductive reasoning with fuzzy parameters in Bayesian networks

Li, Hanlin; Kao, Han-Ying

doi:10.1016/s0305-0548(03)00204-1

Cited by 19 publications

(5 citation statements)

References 7 publications

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“…Their idea is based on evaluating and differentiating arithmetic circuits using a polynomial. Recently Li and Kao (2005) proposed a methodology for solving abductive reasoning problems in BN involving fuzzy parameters and extra constraints. Their method developed a non-linear programming model for dealing with constrained abductive reasoning on BN.…”

Section: Offshore Risk Consideration and Safety Assessment Methodsmentioning

confidence: 99%

An Offshore Risk Analysis Method Using Fuzzy Bayesian Network

Ren

Jenkinson

Wang

et al. 2009

Journal of Offshore Mechanics and Arctic Engineering

142

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The operation of an offshore installation is associated with a high level of uncertainty because it usually operates in a dynamic environment in which technical and human and organizational malfunctions may cause possible accidents. This paper proposes a fuzzy Bayesian network (FBN) approach to model causal relationships among risk factors, which may cause possible accidents in offshore operations. The FBN model explicitly represents cause-and-effect assumptions between offshore engineering system variables that may be obscured under other modeling approaches like fuzzy reasoning and Monte Carlo risk analysis. The flexibility of the method allows for multiple forms of information to be used to quantify model relationships, including formally assessed expert opinions when quantitative data are lacking in early design stages with a high level of innovation or when only qualitative or vague statements can be made. The model is also a modular representation of uncertain knowledge due to randomness and vagueness. This makes the risk and safety analysis of offshore engineering systems more functional and easier in many assessment contexts. A case study of the collision risk between a floating production, storage and offloading unit and the authorized vessels due to human errors during operation is used to illustrate the application of the proposed model.

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Section: Offshore Risk Consideration and Safety Assessment Methodsmentioning

confidence: 99%

An Offshore Risk Analysis Method Using Fuzzy Bayesian Network

Ren

Jenkinson

Wang

et al. 2009

Journal of Offshore Mechanics and Arctic Engineering

142

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“…There are some improvements or combined versions of BN, e.g. combination with fuzzy (Li & Kao, 2005), and many authors deal with further development.…”

Section: Resultsmentioning

confidence: 99%

Joining Analytic Network Process and Bayesian Network Model for Fault Spreading Problem

Szücs¹,

Sallai²

2010

Bayesian Network

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“…The application of abductive reasoning was investigated in a number of disciplines related to OSCM such as operations research (Li and Kao, 2005), computer science (Takeda et al, 1990), cybernetics (Magnani and Li, 2007), econometrics (Zellner, 2007) and organisation science (Mantere and Ketokivi, 2013). Although not in the CR context, abductive reasoning is also familiar to OM research community.…”

Section: Critical Realism: a Primermentioning

confidence: 99%

Can critical realism enable a journey from description to understanding in operations and supply chain management?

Rotaru

Чурилов

Flitman

2014

Supply Chain Management: An International Journal

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Purpose – The current state of theory-building in the field of operations and supply chain management (OSCM) is in a strong need of rigorous, empirically based theories that enhance understanding of the causal relationships between the structural elements and properties of the business processes. In this research note the authors propose the critical realism (CR) philosophy of science as a particularly suitable philosophical position (not to the exclusion of others) to review the mechanisms of OSCM knowledge generation and to provide philosophical grounding and methodological guidance for both OSCM theory building and testing. Design/methodology/approach – To demonstrate potential benefits of CR-based structured approach to knowledge generation in OSCM research, this conceptual paper uses a case study that illustrates the adoption of one of the OSCM theories – i.e. the theory of swift, even flow. Findings – CR interprets the accumulated empirical information about OSCM phenomena as observable manifestations of the underlying causal mechanisms that cannot be perceived otherwise. CR can provide epistemological support to the choice of performance measures that manifest the underlying causal mechanisms of interest. Extensive accumulation of empirical data from multiple innovative sources will not dramatically add to understanding of the system under investigation, unless and until the underlying causal mechanisms that trigger the observed behaviour are identified and tested. The CR abductive mode of reasoning emphasises the role of uncertainty in complex process behaviours and can facilitate enrichment and refutation of OSCM theories. Originality/value – CR has a clear potential to contribute to OSCM research by enabling better understanding of causal relationships underlying complex behaviours of different elements of business process by providing robust and relevant mechanisms of generating knowledge about business processes that explicitly link empirical and causal aspects of theory building and testing.

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Constrained abductive reasoning with fuzzy parameters in Bayesian networks

Cited by 19 publications

References 7 publications

An Offshore Risk Analysis Method Using Fuzzy Bayesian Network

An Offshore Risk Analysis Method Using Fuzzy Bayesian Network

Joining Analytic Network Process and Bayesian Network Model for Fault Spreading Problem

Can critical realism enable a journey from description to understanding in operations and supply chain management?

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