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Banking applications of FCM models

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Banking applications of FCM models
Συγγραφείς: Hatwágner, Miklós F., Vastag, Gyula, Niskanen, Vesa A., Kóczy, László T.
Συνεισφορές: Cornejo, María Eugenia, Kóczy, László T., Medina, Jesús, De Barros Ruano, Antonio Eduardo, Department of Economics and Management
Έτος έκδοσης: 2020
Συλλογή: Helsingfors Universitet: HELDA – Helsingin yliopiston digitaalinen arkisto
Θεματικοί όροι: Bacterial evolutionary algorithm, Banking, Fuzzy cognitive maps, Model uncertainty, Multiobjective optimization, Computer and information sciences
Περιγραφή: Fuzzy Cognitive Map (FCMs) is an appropriate tool to describe, qualitatively analyze or simulate the behavior of complex systems. FCMs are bipolar fuzzy graphs: their building blocks are the concepts and the arcs. Concepts represent the most important components of the system, the weighted arcs define the strength and direction of cause-effect relationships among them. FCMs are created by experts in several cases. Despite the best intention the models may contain subjective information even if it was created by multiple experts. An inaccurate model may lead to misleading results, therefore it should be further analyzed before usage. Our method is able to automatically modify the connection weights and to test the effect of these changes. This way the hidden behavior of the model and the most influencing concepts can be mapped. Using the results the experts may modify the original model in order to achieve their goal. In this paper the internal operation of a department of a bank is modeled by FCM. The authors show how the modification of the connection weights affect the operation of the institute. This way it is easier to understand the working of the bank, and the most threatening dangers of the system getting into an unstable (chaotic or cyclic state) can be identified and timely preparations become possible. © Springer Nature Switzerland AG 2019. ; Peer reviewed
Τύπος εγγράφου: article in journal/newspaper
Περιγραφή αρχείου: application/pdf
Γλώσσα: English
ISBN: 978-3-030-00484-2
978-3-030-00485-9
3-030-00484-8
3-030-00485-6
Relation: Trends in Mathematics and Computational Intelligence; Studies in Computational Intelligence; RIS: urn:E67225250E6AF8BB62AB2049F279B517; https://hdl.handle.net/10138/314650; 85054713528; 000684112300007
Διαθεσιμότητα: https://hdl.handle.net/10138/314650
Rights: info:eu-repo/semantics/openAccess ; openAccess
Αριθμός Καταχώρησης: edsbas.2784E913
Βάση Δεδομένων: BASE
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  – Url: https://hdl.handle.net/10138/314650#
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  Data: Banking applications of FCM models
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  Data: <searchLink fieldCode="AR" term="%22Hatwágner%2C+Miklós+F%2E%22">Hatwágner, Miklós F.</searchLink><br /><searchLink fieldCode="AR" term="%22Vastag%2C+Gyula%22">Vastag, Gyula</searchLink><br /><searchLink fieldCode="AR" term="%22Niskanen%2C+Vesa+A%2E%22">Niskanen, Vesa A.</searchLink><br /><searchLink fieldCode="AR" term="%22Kóczy%2C+László+T%2E%22">Kóczy, László T.</searchLink>
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  Data: Cornejo, María Eugenia<br />Kóczy, László T.<br />Medina, Jesús<br />De Barros Ruano, Antonio Eduardo<br />Department of Economics and Management
– Name: DatePubCY
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  Data: 2020
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  Data: Helsingfors Universitet: HELDA – Helsingin yliopiston digitaalinen arkisto
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  Data: <searchLink fieldCode="DE" term="%22Bacterial+evolutionary+algorithm%22">Bacterial evolutionary algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Banking%22">Banking</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+cognitive+maps%22">Fuzzy cognitive maps</searchLink><br /><searchLink fieldCode="DE" term="%22Model+uncertainty%22">Model uncertainty</searchLink><br /><searchLink fieldCode="DE" term="%22Multiobjective+optimization%22">Multiobjective optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+and+information+sciences%22">Computer and information sciences</searchLink>
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  Data: Fuzzy Cognitive Map (FCMs) is an appropriate tool to describe, qualitatively analyze or simulate the behavior of complex systems. FCMs are bipolar fuzzy graphs: their building blocks are the concepts and the arcs. Concepts represent the most important components of the system, the weighted arcs define the strength and direction of cause-effect relationships among them. FCMs are created by experts in several cases. Despite the best intention the models may contain subjective information even if it was created by multiple experts. An inaccurate model may lead to misleading results, therefore it should be further analyzed before usage. Our method is able to automatically modify the connection weights and to test the effect of these changes. This way the hidden behavior of the model and the most influencing concepts can be mapped. Using the results the experts may modify the original model in order to achieve their goal. In this paper the internal operation of a department of a bank is modeled by FCM. The authors show how the modification of the connection weights affect the operation of the institute. This way it is easier to understand the working of the bank, and the most threatening dangers of the system getting into an unstable (chaotic or cyclic state) can be identified and timely preparations become possible. © Springer Nature Switzerland AG 2019. ; Peer reviewed
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  Data: Trends in Mathematics and Computational Intelligence; Studies in Computational Intelligence; RIS: urn:E67225250E6AF8BB62AB2049F279B517; https://hdl.handle.net/10138/314650; 85054713528; 000684112300007
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    Subjects:
      – SubjectFull: Bacterial evolutionary algorithm
        Type: general
      – SubjectFull: Banking
        Type: general
      – SubjectFull: Fuzzy cognitive maps
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      – SubjectFull: Model uncertainty
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      – SubjectFull: Multiobjective optimization
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      – SubjectFull: Computer and information sciences
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      – TitleFull: Banking applications of FCM models
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