Generalized fuzzy cognitive maps: a new extension of fuzzy cognitive maps

Kang, Bingyi; Mo, Hongming; Sadiq, Rehan; Deng, Yong

doi:10.1007/s13198-016-0444-0

Cited by 9 publications

(7 citation statements)

References 42 publications

(34 reference statements)

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“…Mago et al (2014), for example, tested k = {0.8, 0.7, 0.6, 0.5, 0.45, 0.4, 0.3} and concluded that their system outputs were more accurate for k = 0.7. Kang et al (2016) also state that values of k equal to or close to 1 are ideal, since they provide the possibility of differentiation between the results after convergence, providing better interpretability.…”

Section: Grey Systems Theorymentioning

confidence: 99%

Combining grey clustering and fuzzy grey cognitive maps: an approach to group decision-making on cause-and-effect relationships

Zanon

Carpinetti

2021

Soft Comput

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Fuzzy grey cognitive maps (FGCMs) have been widely adopted to support cause-and-effect decision-making under uncertainty. However, capturing the information for the initial state vector and the relationship matrix from various specialists can be cumbersome, which may affect the convergence of FGCMs or cause them to reach a chaotic state. To address this issue, this paper presents a novel group decision approach based on the combination of grey clustering (GC) and fuzzy grey cognitive maps for assessing causal relationships in uncertain environments. The main contribution consists in applying GC as a mean to obtain the initial state vector from the relationship matrix data. This halves the required inputs to the users, reducing uncertainty in the computational model. Also, the proposition brings a method for aggregating the linguistic judgements of multiple decision-makers when assessing causal relationships. The proposition also differs from others in the literature by providing results with lower imprecision levels, named greyness, and lower number of required iterations for the FGCM-based system to converge. A real application was conducted in a technology start-up to test the approach to practical implications. Results allowed the identification of important elements regarding the company's profile and performance, aiding prioritization and enabling the development of action plans. This paper also includes a comparison of other representative models with the proposed approach, which led to more accurate results. Hence, this study addresses the need for new alternatives to improve the reliability and convergence of FGCM-based systems. Finally, suggestions for future applications are proposed.

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Section: Grey Systems Theorymentioning

confidence: 99%

Combining grey clustering and fuzzy grey cognitive maps: an approach to group decision-making on cause-and-effect relationships

Zanon

Carpinetti

2021

Soft Comput

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“…In the proposed approach, after determining critical risk factors by fault tree analysis, they modeled the system by the FCM relative degree analysis, and the overall safety level was calculated using a fuzzy comprehensive evaluation. Kang et al [67,68] evaluated oil-spill emergency response capability to reduce pollution and accidents. Their proposed approach includes FCM to model the system and calculate weights in the first level, analytic hierarchy process to find the weights in the second level of the distribution model, and fuzzy comprehensive evaluation to measure oil-spill emergency response capability level.…”

Section: Modelingmentioning

confidence: 99%

Fuzzy cognitive maps in systems risk analysis: a comprehensive review

Bakhtavar

Valipour

Yousefi

et al. 2020

Complex Intell. Syst.

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Fuzzy cognitive maps (FCMs) have been widely applied to analyze complex, causal-based systems in terms of modeling, decision making, analysis, prediction, classification, etc. This study reviews the applications and trends of FCMs in the field of systems risk analysis to the end of August 2020. To this end, the concepts of failure, accident, incident, hazard, risk, error, and fault are focused in the context of the conventional risks of the systems. After reviewing risk-based articles, a bibliographic study of the reviewed articles was carried out. The survey indicated that the main applications of FCMs in the systems risk field were in management sciences, engineering sciences and industrial applications, and medical and biological sciences. A general trend for potential FCMs’ applications in the systems risk field is provided by discussing the results obtained from different parts of the survey study.

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“…In this equation, the lambda value corresponds to a constant defined by the system designer. Kang et al (2016) state that values of λ equal to or close to 1 are ideal, since they provide the possibility of differentiation between the results after convergence of the system, providing better interpretability. In summary, the system activation consists in iteratively multiplying the initial state vector and the relationship matrix within the chosen activation function, used to monotonically map these values evolution.…”

Section: Fuzzy Cognitive Mapsmentioning

confidence: 99%

The relationship between organizational culture and the performance of a technology startup: A Fuzzy Cognitive Maps based analysis

Zanon

Lisboa²,

Carpinetti³

2020

GEPROS

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New organizations, such as startups, are more exposed to failure due to their vulnerability when arriving the market. Therefore, monitoring and managing performance indicators becomes essential, since they enable the achievement of strategic objectives. However, this process is impacted by the organizational culture, which guides the company's behavioral patterns. Therefore, this paper proposes the use of fuzzy cognitive maps to quantify the causal relations between Hofstede's cultural dimensions and the performance of a technology startup. The employed methodology is composed of three stages: literature review, computational model development and conduction of an illustrative application. It is classified as quantitative, axiomatic and normative, since it proposes a model from the identified gaps and the opinions of specialists, suggesting an approach that integrates the research concepts. The results indicate that the time for development is the most impacted indicator by culture. It can be concluded, therefore, that it was possible to consider the inherent subjectivity to the evaluation of the causal relations between culture and performance by applying the fuzzy cognitive map. Hence, action plans can be proposed to foster improvement initiatives that promote the culture-performance alignment.

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Generalized fuzzy cognitive maps: a new extension of fuzzy cognitive maps

Cited by 9 publications

References 42 publications

Combining grey clustering and fuzzy grey cognitive maps: an approach to group decision-making on cause-and-effect relationships

Combining grey clustering and fuzzy grey cognitive maps: an approach to group decision-making on cause-and-effect relationships

Fuzzy cognitive maps in systems risk analysis: a comprehensive review

The relationship between organizational culture and the performance of a technology startup: A Fuzzy Cognitive Maps based analysis

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