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  • Search: subject:"fuzzy c-means algorithm"
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Year of publication
Subject
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Algorithm 2 Algorithmus 2 Cluster analysis 2 Fuzzy c-means algorithm 2 Fuzzy sets 2 Fuzzy-Set-Theorie 2 fuzzy c-means algorithm 2 fuzzy sets 2 pattern recognition 2 AHP approach 1 AHP-Verfahren 1 Adaptive neuro-fuzzy inference system (ANFIS) 1 Analytic hierarchy process 1 Clusteranalyse 1 Convergence 1 Decision 1 Decision support system 1 Earthquake prediction 1 Economic growth 1 Entscheidung 1 FCM 1 Fuzzy C-means algorithm (FCM) 1 Fuzzy logic 1 Human Resource Management 1 Human resources 1 Human resources analytics 1 Humanressourcen 1 IDAR 1 IFT 1 Intuitionistic Fuzzy TOPSIS 1 Management information system 1 Management-Informationssystem 1 Moment magnitude 1 Multi-criteria analysis 1 Multi-criteria decision-making 1 Multikriterielle Entscheidungsanalyse 1 Neutrosophic sets 1 Optimization 1 Partitioning Algorithms 1 Pattern recognition 1
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Online availability
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Undetermined 3 Free 2 CC license 1
Type of publication
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Article 5 Book / Working Paper 1
Type of publication (narrower categories)
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Article in journal 2 Aufsatz in Zeitschrift 2
Language
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English 3 Undetermined 3
Author
All
Bezdek, James 1 Devi, P. Meenakshi 1 Draeseke, Robert 1 Giles, David E. A. 1 Giles, David EA 1 Hathaway, Richard 1 Mirrashid, Masoomeh 1 Santhosh, A. V. 1 Sharmila, B. 1 Yiğit, Fatih 1
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Institution
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Department of Economics, University of Victoria 1
Published in...
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Decision analytics journal 1 Econometrics Working Papers 1 International journal of business information systems : IJBIS 1 Journal of Classification 1 Natural Hazards 1 The Journal of International Trade & Economic Development 1
Source
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RePEc 4 ECONIS (ZBW) 2
Showing 1 - 6 of 6
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A three-stage fuzzy neutrosophic decision support system for human resources decisions in organizations
Yiğit, Fatih - In: Decision analytics journal 7 (2023), pp. 1-11
This study proposes an integrated Decision Support System (DSS) with Multi-Criteria Decision-Making (MCDM) to evaluate trainers in organizations and choose the most suitable one(s) for a training program. The clustering stage determines the most appropriate number of trainees to be assigned to a...
Persistent link: https://www.econbiz.de/10014505298
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Efficient enhanced intrusion identification and response system for MANETs
Santhosh, A. V.; Devi, P. Meenakshi; Sharmila, B. - In: International journal of business information systems : … 29 (2018) 4, pp. 535-546
Persistent link: https://www.econbiz.de/10011981384
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Earthquake magnitude prediction by adaptive neuro-fuzzy inference system (ANFIS) based on fuzzy C-means algorithm
Mirrashid, Masoomeh - In: Natural Hazards 74 (2014) 3, pp. 1577-1593
This paper investigates the prediction of future earthquakes that would occur with magnitude 5.5 or greater using adaptive neuro-fuzzy inference system (ANFIS). For this purpose, the earthquake data between 1950 and 2013 that had been recorded in the region with 2°E longitude and 4°N latitude...
Persistent link: https://www.econbiz.de/10011151592
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Econometric Modelling based on Pattern recognition via the Fuzzy c-Means Clustering Algorithm
Giles, David E. A.; Draeseke, Robert - Department of Economics, University of Victoria - 2001
based on the Fuzzy c-Means algorithm that is widely used in the context of pattern recognition, and the Takagi …
Persistent link: https://www.econbiz.de/10005800941
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Output Convergence and International Trade: Time-Series and Fuzzy Clustering Evidence for New Zealand and her Trading Partners, 1950 - 1992
Giles, David EA - In: The Journal of International Trade & Economic Development 14 (2005) 1, pp. 93-114
Using historical time-series data, we test for convergence and common trends in real per capita output for New Zealand and her four major trading partners. Both bivariate and multivariate time-series methods are used, and we also implement the fuzzy c-means clustering algorithm as a new method...
Persistent link: https://www.econbiz.de/10005463006
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Recent convergence results for the fuzzy c-means clustering algorithms
Hathaway, Richard; Bezdek, James - In: Journal of Classification 5 (1988) 2, pp. 237-247
Persistent link: https://www.econbiz.de/10005602948
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