Emergency management for a nuclear power plant using fuzzy cognitive maps

Espinosa-Paredes, Gilberto; Nuñez-Carrera, Alejandro; Laureano-Cruces, Ana Lilia; Vázquez–Rodríguez, A.; Espinosa-Martínez, É.-G.

doi:10.1016/j.anucene.2008.07.007

Cited by 13 publications

(11 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Medicine including diagnosis method for tumour grading (Papageorgiou et al, 2006) and specific language impairment (Georgopoulos et al, 2003), strategic planning (C¸oban and Sec¸me, 2002;Yaman and Polat, 2009), energy management studies especially focusing on the management of nuclear power plants (Espinosa-Paredes et al, 2008) are other different topics in which FCM used as a modelling tool.…”

Section: Fuzzy Cognitive Mapping (Fcm)mentioning

confidence: 99%

Analyzing critical success factors of total quality management by using fuzzy cognitive mapping

Kutlu

Kadaifçi

2014

Journal of Enterprise Information Management

View full text Add to dashboard Cite

Purpose – Total quality management (TQM) is a process and philosophy to achieve customer satisfaction in long term by improving the products, processes and services effectively and efficiently. TQM implementation is turning into a complex practice due to the increasing number of effective factors and key elements labelled as critical success factors (CSFs). The purpose of this paper is to analyse the relations between CSFs of TQM and to provide decision makers has a clear picture of relations by determining the most affecting – both the number of CSFs which this factor affects and the its effect degree on relevant CSFs are higher comparing to other factors – of this factors affected factors – both the number of CSFs and their effect degree on these factors are higher – that influences a successful TQM implementation. Design/methodology/approach – The paper refers to fuzzy cognitive maps (FCMs) that allow dynamic modelling of a system in consideration of a complex network structure and the effects of factors to each other. The method demonstrates causal representations between CSFs under uncertainty to represent the relations and interaction between them and performs qualitative simulations to analyse the factors that have the highest impact on continuous improvement of quality management process. The evaluations are performed by five academicians whose professions are on both the areas of TQM and FCM. Findings – FCM analysis shows how the most affecting and affected factors influence the other CSF in order to manage a successful TQM implementation. Originality/value – The critical factors of TQM implementation are in the focus of most of the empirical studies in the literature. However, none of them considers the dynamic interactions between the factors. This study employs FCM to explore the CSFs that influence the TQM implementation process considering the relations among them to observe the most affecting and affected factors based on the changes of determined CSFs.

show abstract

Section: Fuzzy Cognitive Mapping (Fcm)mentioning

confidence: 99%

Analyzing critical success factors of total quality management by using fuzzy cognitive mapping

Kutlu

Kadaifçi

2014

Journal of Enterprise Information Management

View full text Add to dashboard Cite

show abstract

“…In FCMs, knowledge or concepts are structured as a web of relationships that is similar to both human reasoning and the human decision‐making process (Furfaro et al, ). FCMs have been successfully used in a variety of applications, mostly in the biomedical (Papageorgiou et al, , ), industrial (Stylios and Groumpos, ), causal inference (Miao and Liu, 2000) and engineering fields (Espinosa‐Paredes et al, ). To the authors' knowledge, FCM's have only been used in geomorphology to identify cryovolcanism on Titan (Furfaro et al, ).…”

Section: Fuzzy Cognitive Maps Of Aeolian Landscape Instabilitymentioning

confidence: 99%

Characterizing instability of aeolian environments using analytical reasoning

Houser

Bishop

Barrineau

2014

Earth Surf Processes Landf

View full text Add to dashboard Cite

This short communication describes the development and application of analytical reasoning to quantify instability of an aeolian environment using scale-dependent information coupled with conceptual knowledge of process and feedback mechanisms. Specifically, a simple Fuzzy Cognitive Map (FCM) for aeolian landscape instability was developed that represents conceptual knowledge of key biophysical processes and feedbacks. Model inputs include satellite-derived surface biophysical and geomorphometric parameters. FCMs are a knowledge-based artificial intelligence (AI) technique that merges fuzzy logic and neural computing in which knowledge or concepts are structured as a web of relationships that is similar to both human reasoning and the human decision-making process. Given simple process-form relationships, the analytical reasoning model is able to map the influence of land management practices and the geomorphology of the inherited surface on aeolian instability within the South Texas Sand Sheet. Results suggest that FCMs can be used to formalize process-form relationships and information integration analogous to human cognition with future iterations accounting for the spatial interactions and temporal lags across the sand sheets.

show abstract

“…The use of FCMs is extended in various technology fields. FCMs have been used to analyze electric circuits [51], to model and support control systems [52], to represent failure models and affect the analysis of a model system [53], etc. The FCM constitutes a modeling methodology based on human knowledge.…”

Section: Fuzzy Cognitive Mapsmentioning

confidence: 99%