IDENTYFIKACJA PRZEPŁYWU DWUFAZOWEGO GAZ-CIECZ OPARTA NA OCENIE ROZMYTEJ OBRAZÓW TOMOGRAFICZNYCH 3D

Al-sharhan S. , Karray F. , Gueaieb W., Basir O.: Fuzzy entropy: a brief survey in Fuzzy Systems. The 10th IEEE International Conference on, vol. 3, 2001, pp. 1135-1139.
  Google Scholar

Banasiak R. , Wajman R. , Fidos H. , Fiderek P. , Jaworski T. , Nowakowski J. , Sankowski D. : System trójwymiarowej tomografii pojemnościowej w zastosowaniu do wyznaczania udziału faz oraz identyfikacji struktur w przepływach mieszanin gaz-ciecz. IAPGOS, 2013, nr 3, 28-31.
DOI: https://doi.org/10.35784/iapgos.1459   Google Scholar

Caniere H. , Bauwens B. , T’Joen C. , and Paepe M. D.: Probabilistic mapping of adiabatic horizontal two-phase flow by capacitance signal feature clustering. International Journal of Multiphase Flow, vol. 35, no. 7, 2009, pp. 650 – 660.
DOI: https://doi.org/10.1016/j.ijmultiphaseflow.2009.03.006   Google Scholar

Cho K.-H., Kim S. , Lee Y.-J.: A fast eit image reconstruction method for the two-phase flow visualization. International Communications in Heat and Mass Transfer, vol. 26, no. 5, 1999, pp. 637 – 646.
DOI: https://doi.org/10.1016/S0735-1933(99)00050-0   Google Scholar

Cho K. H., Kim S. , Lee Y. J.: Impedance imaging of two-phase flow field with mesh grouping method. Nuclear Engineering and Design, vol. 204, no. 1–3, 2001, pp. 57 – 67.
DOI: https://doi.org/10.1016/S0029-5493(00)00320-4   Google Scholar

Cortes C. and Vapnik V. , Support-vector networks. Mach. Learn., vol. 20, Sept. 1995, pp. 273–297.
DOI: https://doi.org/10.1007/BF00994018   Google Scholar

Dunn J. C.: A fuzzy relative of the ISODATA process and its use in detecting compact Well-Separated clusters. Journal of Cybernetics, vol. 3, no. 3, 1973, pp. 32–57.
DOI: https://doi.org/10.1080/01969727308546046   Google Scholar

Evgeniou T. , Pontil M. and Elisseeff A.: Leave one out error, stability, and generalization of voting combinations of classifiers. Mach. Learn., vol. 55, Apr. 2004, pp. 71–97.
DOI: https://doi.org/10.1023/B:MACH.0000019805.88351.60   Google Scholar

Guyon I. , Weston J. , Barnhill S. , Vapnik V.: Gene selection for cancer classification using support vector machines. Mach. Learn., vol. 46, Mar. 2002, pp. 389–422.
DOI: https://doi.org/10.1023/A:1012487302797   Google Scholar

Kohavi R. and Provost F.: Glossary of terms. Machine Learning, vol. 30, pp. 271–274, 1998. 10.1023/A:1017181826899.
DOI: https://doi.org/10.1023/A:1007442505281   Google Scholar

Li H. , Zhou Z. , Hu C.: Measurement and evaluation of two-phase flow parameters. Instrumentation and Measurement, IEEE Transactions on, vol. 41, apr 1992, pp. 298 –303.
DOI: https://doi.org/10.1109/19.137364   Google Scholar

Rahmat M. F., Kamaruddin N. S., Isa M. D.: Flow regime identification in pneumatic conveyor using electrodynamic transducer and fuzzy logic method. Journal on Smart Sensing and Intelligent Systems, vol. 2, 2009, pp. 396–416.
DOI: https://doi.org/10.21307/ijssis-2017-357   Google Scholar

Rifkin R. and Klautau A.: In defense of one-vs-all classification. J. Mach. Learn. Res., vol. 5, Dec. 2004, pp. 101–141.
  Google Scholar

Tsoukalas L. H., Ishii M. , and Mi Y.: A neurofuzzy methodology for impedance-based multiphase flow identification. Engineering Applications of Artificial Intelligence, vol. 10, no. 6, 1997, pp. 545 – 555.
DOI: https://doi.org/10.1016/S0952-1976(97)00037-7   Google Scholar

Wajman R. , Banasiak R.: Nowa metoda tunelowego wyznaczania macierzy wrażliwości dla potrzeb procesu rekonstrukcji obrazów dla trójwymiarowej tomografii pojemnościowej. IAPGOS, 2013, nr 3, 32-37.
DOI: https://doi.org/10.35784/iapgos.1460   Google Scholar