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Crisp and Fuzzy Classifiers in the Two-Phase Gas-Liquid Flow Diagnostics

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EN
Abstrakty
EN
The following paper presents results of common clustering algorithms use, both crisp and fuzzy, for flow pattern recognition of two-phase gas-liquid flows observed in horizontal pipeline. Obtained results of HCM, FCM, and kNN clustering algorithms were presented in a form of confusion matrix and compared via its prediction performance.
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autor
  • Lodz University of Technology, Lodz, Poland
autor
  • Lodz University of Technology, Lodz, Poland
autor
  • Lodz University of Technology, Lodz, Poland
autor
  • Lodz University of Technology, Lodz, Poland
Bibliografia
  • [1] L. Chen, G. Guo, S. Wang, Nearest neighbor classification by partially fuzzy clustering, Proceedings - 26th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012
  • [2] C. Correa, C. Valero, P. Barreiro, M.P. Diago, J. Tardáguila, Feature extraction on vineyard by Gustafson Kessel FCM and K-means, Proceedings of the Mediterranean Electrotechnical Conference, MELECON 2012
  • [3] P. Górecki, K. Sopyła, P. Drozda, Ranking by Kmeans voting algorithm for similar image retrieval, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7267 LNAI (PART 1), pp. 509-517, 2012
  • [4] Z. Ji, Y. Xia, Q. Chen, Q. Sun, D. Xia, D.D. Feng, Fuzzy c-means clustering with weighted image patch for image segmentation, Applied Soft Computing Journal, Vol. 12, No. 6, pp. 1659-1667, 2012
  • [5] S.R. Kannan, S. Ramathilagam, P.C. Chung, Effective fuzzy c-means clustering algorithms for data clustering problems, Expert Systems with Applications, Vol. 39, No. 7, pp. 6292-6300, , 2012
  • [6] P.Y. Mok, H.Q. Huang, Y.L. Kwok, J.S. Au, A robust adaptive clustering analysis method for automatic identification of clusters, Pattern Recognition, Vol. 45, No. 8, pp. 3017-3033, 2012
  • [7] L. Rutkowski, Metody i techniki sztucznej inteligencji, Wydawnictwo Naukowe PWN, Warszawa, 2009
  • [8] D.A. Zighed, D. Ezzeddine, F. Rico, Neighborhood random classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7301 LNAI (PART 1), pp. 98-108, 2012
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ca474b7d-e9fc-4417-ad01-3481179e30e7
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