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USING CLUSTERING IN GEOSCIENCES: EXAMPLES AND CASE STUDIES

Marek, Lukas, Paszto, Vit, TUCEK, Pavel

First published: 2015https://doi.org/10.5593/sgem2015/b22/s11.150View metrics

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Title
USING CLUSTERING IN GEOSCIENCES: EXAMPLES AND CASE STUDIES
Authors
Marek, Lukas, Paszto, Vit, TUCEK, Pavel
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 15th International Multidisciplinary Scientific GeoConference SGEM2015, INFORMATICS, GEOINFORMATICS AND REMOTE SENSING
Publisher
Stef92 Technology
Year
2015
Pages
1207-1214
ISSN
1314-2704
ISBN
978-619-7105-35-3
Language
en
Publication type
Conference Paper
References30

  1. Beale, L. et al.: Methodologic issues and approaches to spatial epidemiology. Environ. Health Perspect. 116, 8, 1105– 10 (2008).

  2. Bencko, V. et al.: Statistické metody v epidemiologii. Nakladatelství Karolinum, Praha (2003).

  3. Florek, K. et al.: Sur la Liaiso n et la Division des Points d’un Ensemble Fini. Colloq. Math. 2, 3-4, 282– 285 (1951).

  4. Hastings, H.M., Sugihara, G.: Fractals: A User’s Guide for the Natural Sciences. Oxford University Press, Oxford (1994).

  5. Hebák, P. et al.: Vícerozměrné statistické metody 2. Informatorium, Praha (2005).

  6. Horák, J.: Prostorové analýzy dat. VŠB -TU Ostrava, HGF, Institut geoinformatiky, Ostrava (2011).

  7. Chen, C. et al.: SpatialEpi: Methods and Data for Spatial Epidemiology, http://cran.r- project.org/package=SpatialEpi, (2014).

  8. Kitchin, R., Thrift, N. eds: International encyclopedia of human geography. Elsevier Science (2009).

  9. Knighton, D.: Fluvial Forms and Processes: A New Perspective. Oxford University Press, New York (1998).

  10. Kumar, P., Wasan, S.K.: Comparative study of K-means, pam and rough K-means algorithms using cancer datasets. Proceedings of CSIT: 2009 International Symposium on Computing, Communication, and Control (ISCCC 2009). pp. 136 – 140 (2009).

  11. Marek, L. et al.: On Estimation of the Spatial Clustering: Case Study of Epidemiological Data In Olomouc Region, Czech Republic. VŠB – Technická univerzita Ostrava, Ostrava (2013).

  12. Marek, L. et al.: Space-time evaluation of health data: Case of Olomouc area, Czech Republic. SGEM2013 Conference Proceedings. pp. Vol. 1, 911 –918 STEF92 Technology Ltd., Sofia, Bulgaria (2013).

  13. Park, H.S., Jun, C.H.: A simple and fast algorithm for K-medoids clustering. Expert Syst. Appl. 36, 2, 3336– 3341 (2009).

  14. Peitgen, H.-O. et al.: Chaos and Fractals Mew Frontiers of Science. Springer, New York (2004).

  15. Tobler, W.R.: A Computer Movie Simulation Urban Growth in the Detroit Region. Econ. Geogr. 46, 332, 234–240 (1970). International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org

  16. Beale, L. et al.: Methodologic issues and approaches to spatial epidemiology. Environ. Health Perspect. 116, 8, 1105– 10 (2008).

  17. Bencko, V. et al.: Statistické metody v epidemiologii. Nakladatelství Karolinum, Praha (2003).

  18. Florek, K. et al.: Sur la Liaiso n et la Division des Points d’un Ensemble Fini. Colloq. Math. 2, 3-4, 282– 285 (1951).

  19. Hastings, H.M., Sugihara, G.: Fractals: A User’s Guide for the Natural Sciences. Oxford University Press, Oxford (1994).

  20. Hebák, P. et al.: Vícerozměrné statistické metody 2. Informatorium, Praha (2005).

  21. Horák, J.: Prostorové analýzy dat. VŠB -TU Ostrava, HGF, Institut geoinformatiky, Ostrava (2011).

  22. Chen, C. et al.: SpatialEpi: Methods and Data for Spatial Epidemiology, http://cran.r- project.org/package=SpatialEpi, (2014).

  23. Kitchin, R., Thrift, N. eds: International encyclopedia of human geography. Elsevier Science (2009).

  24. Knighton, D.: Fluvial Forms and Processes: A New Perspective. Oxford University Press, New York (1998).

  25. Kumar, P., Wasan, S.K.: Comparative study of K-means, pam and rough K-means algorithms using cancer datasets. Proceedings of CSIT: 2009 International Symposium on Computing, Communication, and Control (ISCCC 2009). pp. 136 – 140 (2009).

  26. Marek, L. et al.: On Estimation of the Spatial Clustering: Case Study of Epidemiological Data In Olomouc Region, Czech Republic. VŠB – Technická univerzita Ostrava, Ostrava (2013).

  27. Marek, L. et al.: Space-time evaluation of health data: Case of Olomouc area, Czech Republic. SGEM2013 Conference Proceedings. pp. Vol. 1, 911 –918 STEF92 Technology Ltd., Sofia, Bulgaria (2013).

  28. Park, H.S., Jun, C.H.: A simple and fast algorithm for K-medoids clustering. Expert Syst. Appl. 36, 2, 3336– 3341 (2009).

  29. Peitgen, H.-O. et al.: Chaos and Fractals Mew Frontiers of Science. Springer, New York (2004).

  30. Tobler, W.R.: A Computer Movie Simulation Urban Growth in the Detroit Region. Econ. Geogr. 46, 332, 234–240 (1970). International Multidisciplinary Scientific GeoConfenferences SGEM 2015 www.sgem.org

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