A fuzzy cognitive map approach for effect-based operations: An illustrative case

Yaman, Dilek; Polat, Seçkin

doi:10.1016/j.ins.2008.10.013

Cited by 112 publications

(54 citation statements)

References 60 publications

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“…Activation functions such as the sigmoid, hyperbolic tangent, step and threshold linear can be used in the FCM inference process (20), (21), (22).…”

Section: Fuzzy Cognitive Maps (Fcms)mentioning

confidence: 99%

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2018

European Journal of Engineering and Formal Sciences

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The failure rate of an Information Technologies (IT) software project is pretty high because of their uncertain and risky structure. Managing well this kind of projects becomes important. Failure Mode and Effect Analysis (FMEA) is an extensive method that is used for identifying the importance level of risks in a project by using risk priority numbers (RPN). This method is based on experts' experience and cognitive skills at gathering data in order to make risk assessment. This situation causes inaccurate conclusions in the final risk ranking. Fuzzy logic is widely integrated into FMEA to handle these inaccuracies and inconsistencies in the literature while making assessment and calling Fuzzy FMEA method that we proposed. In this study, we explored another uncovered weaknesses of the proposed method. FMEA and Fuzzy FMEA do not consider the relationships among the risks of a project. To overcome this disadvantage, we proposed to integrate the idea of cognitive maps into these two methods (FMEA w/FCMs and Fuzzy FMEA w/FCMs). Finally, we got a comprehensive risk assessment methodology by considering the relationships among the risks under ambiguous circumstances.

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“…Activation functions such as the sigmoid, hyperbolic tangent, step and threshold linear can be used in the FCM inference process (20), (21), (22).…”

Section: Fuzzy Cognitive Maps (Fcms)mentioning

confidence: 99%

Untitled

2018

European Journal of Engineering and Formal Sciences

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“…Carlucci et al 2013). This type of cognitive mapping has since been applied in a wide range of different decision situations (an extensive deliberation falls outside of the scope of this paper; but for further discussion, see Tsadiras et al 2003;Kok 2009;Salmeron 2009;Yaman and Polat 2009;Papageorgiou et al 2012;Salmeron 2012).…”

Section: Background On Fuzzy Cognitive Mappingmentioning

confidence: 99%

“…The weights of the links (or arcs) can also be a fuzzy value within [-1, 1] (or follow a trivalent logic within {-1, 0, 1}). As such, there are three types of causal relationships between concepts: (a) negative causality (W ij \ 0), meaning that an increase (decrease) in the value of C i will lead to a decrease (increase) in the value of C j ; (b) null causality (W ij = 0), meaning that no relationship exists between C i and C j ; and (c) positive causality (W ij [ 0), which occurs when an increase (decrease) in the value of C i leads to an increase (decrease) in the value of C j (for details, see Kim and Lee 1998;Mazlack 2009;Kok 2009;Salmeron 2009;Yaman and Polat 2009).…”

Section: Background On Fuzzy Cognitive Mappingmentioning

confidence: 99%

Understanding the dynamics behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping

et al. 2015

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Using fuzzy cognitive mapping, this study aims to create a holistic framework whereby the determinants of bank branch service quality and their cause-and-effect relationships can be identified and dynamically analyzed. The methodology is applied using a group of experts from the banking industry in Portugal. Our results not only indicate the applicability and usefulness of the proposed approach, but identify human resource characteristics (which include collaborators' personal and professional training) and management team technical skills as particularly relevant driving forces of bank branch service quality. The proposal holds great potential for the operational planning and improvement of bank branch service quality, which is a prime concern for bank administrators, bank branch collaborators, and society at large. Advantages and shortcomings of the framework are also reported.

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“…Models established by a single expert are vulnerable to bias and inaccuracy. Credibility of modelling with FCMs can be improved by aggregating maps from multiple experts [111]. Thus, FCMs allow for a relatively simple knowledge aggregation, obtained from several experts.…”

Section: Aggregating Procedures For Fuzzy Cognitive Mapsmentioning

confidence: 99%

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

León¹,

Nápoles²,

Bello³

et al. 2013

IJCIS

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Although the individuals" transport behavioural modelling is a complex task, it can produce a notable social and economic impact. In this paper, Fuzzy Cognitive Maps are explored to represent the behaviour and operation of such complex systems. An automatic approach to extract mental representations from individuals and convert them into computational structures is defined. For the creation of knowledge bases the use of Knowledge Engineering is accounted and later on the data is transferred into structures based on Fuzzy Cognitive Maps. Once the maps are created, their performances get improved through the use of a Particle Swarm Optimisation algorithm as a learning method, readjusting its predicting capacity from stored scenarios, where individuals left their preferences in front of random situations. Another important result is clustering the maps for knowledge discovery. This permits to find useful groups of individuals that policymakers can use for simulating new rules and policies. After related maps are identified, to merge them as a unique structure could benefit for different usages. Therefore an aggregating procedure is elaborated for this task, constituting an alternative approach for selecting a centroid of a specific estimated group, and therefore having, in only one structure, the knowledge and behavioural acting from a collection of individuals. Learning, clustering and aggregation of Fuzzy Cognitive Maps are combined in a cascade experiment, with the intention of describing travellers" behaviour and change trends in different abstraction levels. The results of this approach will help transportation policy decision makers to understand the people"s needs in a better way, consequently will help them actualising different policy formulations and implementations.

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A fuzzy cognitive map approach for effect-based operations: An illustrative case

Cited by 112 publications

References 60 publications

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Understanding the dynamics behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

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