УДК 004.93

КЛАСТЕРИЗАЦИЯ ПОСЛЕДОВАТЕЛЬНОСТЕЙ ВИДЕОДАННЫХ НА ОСНОВЕ
ГАРМОНИЧЕСКИХ k-СРЕДНИХ

Машталир Сергей Владимирович,
доктор техн. наук, профессор кафедры Харьковского национального университета радиоэлектроники,
 sergii.mashtalir@nure.ua

Столбовой Михаил Иванович,
аспирант Харьковского национального университета радиоэлектроники,  st.mihail92@gmail.com

Яковлев Сергей Всеволодович,
доктор физ.-мат. наук, профессор, профессор кафедры Национального аэрокосмического университета
им. Н.Е. Жуковского «Харьковский авиационный институт»,  svsyak7@gmail.com

СПИСОК ЛИТЕРАТУРЫ

1. Gan G., Ma C., Wu J. Data clustering: Theory, algorithms and applications. Philadelphia: SIAM, 2007. 466 p.


2. Jain A.K., Dubes R.C. Algorithms for clustering data. Englewood Cliffs, N.J.: Prentice Hall, 1988. 320 p.


3. Olson D.L., Dursun D. Advanced data mining techniques. Berlin: Springer, 2008. 180 p.


4. Hulianytskyi L., Malyshko S. Big data in information analytical system “NEWSCAPE”. In: Data Stream Mining & Processing: Proc. IEEE First Int. Conf. on Data Stream Mining & Processing (23–27 August, 2016, Lviv, Ukraine) 2016. P. 382–386.


5. Hulianytskyi L., Riasna I. Formalization and classification of combinatorial optimization problems. Optimization Methods and Its Applications. 2017. Vol. 130. P. 239–250.


6. Hulianytskyi L., Riasna I. Automatic classification method based on a fuzzy similarity relation. Cybernetics and Systems Analysis. 2016. Vol. 52, N 1. P. 30–37.


7. Ведмедь А.Г., Машталир С.В., Сакало Е.С. Матричный алгоритм самообучения карты Кохонена в задачах обработки изображений. Системи управління, навігації та зв’язку. 2009. Вип. 1. С. 188–192.


8. Bodyanskiy Ye., Volkova V., Skuratov M. Matrix neuro-fuzzy self-organizing clustering network. Scientific Journal of Riga Technical University. Computer Science. Information Technology and Management Science. 2011. Vol. 49. P. 54–58.


9. Mashtalir V.P., Yakovlev S.V. Point-set methods of clusterization of standard information. Cybernetics and Systems Analysis. 2001. Vol. 37, N 3. P. 295–307.


10. Han J., Kamber M. Data mining: Concepts and techniques. San Francisco: Morgan Kaufmann, 2006. 26 p.


11. Xu R., Wunsch D. Survey of clustering algorithms. IEEE Transactions on Neural Networks. 2005. Vol. 16, N 3. P. 645–678.


12. Gngr Z., nler A. K-harmonic means data clustering with tabu-search method. Applied Mathematical Modelling. 2008. Vol. 32, N 6. P. 1115–1125.


13. Zhang B., Hsu M., Dayal V. K-harmonic means: A spatial clustering algorithm with boosting. First International Workshop on Temporal, Spatial and Spatio-Temporal Data Mining, 2000. P. 31–45.


14. Abonyi J., Feil B., Nemeth S., Arva P. Fuzzy clustering based segmentation of timeseries. Lecture Notes in Computer Science. 2003. Vol. 2810. P. 275–285.


15. Liao T.W. Clustering of time series data: A survey. Pattern Recognition. 2005. Vol. 38, N 11. P. 1857–1874.


16. Berndt D.J., Clifford J. Using dynamic time warping to find patterns in time series. In: Proc. 3rd International Conference on Knowledge Discovery and Data Mining. KDD Workshop. 1994. P. 359–370.


17. Setlak G., Bodyanskiy Y., Pliss I., Vynokurova O., Peleshko D., Kobylin I. Adaptive fuzzy clustering of multivariate short time series with unevenly distributed observations based on matrix neuro-fuzzy self-organizing network. Advances in Intelligent Systems and Computing. 2018. Vol. 643. P. 308–315.


18. Bodyanskiy Y., Kobylin I., Rashkevych Y., Vynokurova O., Peleshko D. Hybrid fuzzy clustering algorithm of unevenly and asynchronically spaced time series in computer engineering. In: Proc. 14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (20–24 February 2018, Lviv–Slavske, Ukraine). P. 930–935.


19. Chu S., Keogh E., Hart D., Pazzani M. Iterative deepening dynamic time warping for time series. In: Proc. of the 2nd SIAM International Conference on Data Mining, 2002. P. 195–212.


20. Gerasin S.N., Shlyakhov V.V., Yakovlev S.V. Set coverings and tolerance relations. Cybernetics and Systems Analysis. 2008. Vol. 43, N 3. P. 333–340.


21. Stoyan Y.G., Yakovlev S.V. Configuration space of geometric objects. Cybernetics and Systems Analysis. 2018. Vol. 54, N 5. P. 716–726.


22. Yakovlev S.V. On some classes of spatial configurations of geometric objects and their formalization. Journal of Automation and Information Sciences. 2018. Vol. 50, N 9. P. 38–50.