Using advanced data mining and integration in environmental prediction scenarios

• Autorzy: Habala O. , Hluchy L. , Tran V. , Krammer P. , Seleng M.
• Języki publikacji: EN

Abstrakty

EN

We present one of the meteorological and hydrological experiments performed in the FP7 project ADMIRE. It serves as an experimental platform for hydrologists, and we have used it also as a testing platform for a suite of advanced data integration and data mining (DMI) tools, developed within ADMIRE. The idea of ADMIRE is to develop an advanced DMI platform accessible even to users who are not familiar with data mining techniques. To this end, we have designed a novel DMI architecture, supported by a set of software tools, managed by DMI process descriptions written in a specialized high-level DMI language called DISPEL, and controlled via several different user interfaces, each performing a different set of tasks and targeting different user group.

Słowa kluczowe

EN

data mining; data integration; meteorology; hydrology

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2012
• Tom: Vol. 13 (1)
• Strony: 5--16
• Opis fizyczny: Bibliogr. 15 poz., rys.

Twórcy

autor

Habala O.

• Institute of Informatics of the Slovak Academy of Sciences, Bratislava, Slovakia

autor

Hluchy L.

• Institute of Informatics of the Slovak Academy of Sciences, Bratislava, Slovakia

autor

Tran V.

• Institute of Informatics of the Slovak Academy of Sciences, Bratislava, Slovakia

autor

Krammer P.

• Institute of Informatics of the Slovak Academy of Sciences, Bratislava, Slovakia

autor

Seleng M.

• Institute of Informatics of the Slovak Academy of Sciences, Bratislava, Slovakia

Bibliografia

• [1] Bartok J., Habala O., Bednar P., Gazak M., Hluchy L.: Data Mining and Integration for Predicting Significant Meteorological Phenomena. [in:] Proc. of ICCS 2010 — International Conference on Computational Science, vol. 1 of Procedia Computer Science, pp. 37–46. Elsevier Science BV, 2010.
• [2] Brezany P., Aranda C. B., Corcho O., Janciak I., Woehrer A., Atkinson M.: ADMIRE – Report Defining the Final Iteration of the Model and Language. Deliverable report D1.9, The ADMIRE Project, May 2011.
• [3] Ciglan M., Habala O., Tran V., Hluchy L., Kremler M., Gera M.: Application of ADMIRE Data Mining and Integration Technologies in Environmental Scenarios. [in:] R. Wyrzykowski, J. Dongarra, K. Karczewski and J. Wasniewski (Eds.), Parallel Processing and Applied Mathematics, Part II, volume 6068 of Lecture Notes in Computer Science, pp. 165–173. Springer-Verlag Berlin, 2010.
• [4] EU Parliament: Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE). Official Journal of the European Union, 50(L108), April 2007.
• [5] Galea M., Atkinson M., Liew C. S., Martin P.: emphADMIRE – Final Report on the ADMIRE Architecture, May 2011.
• [6] Habala O., Maliˇska M., Hluch´y L.: Service-based flood forecasting simulation cascade in k-wf grid. [in:] M. Bubak, S. Unger (Eds.), Cracow 06 Grid Workshop : K-Wf Grid, pp. 138–145. Academic Computer Centre CYFRONET AGH, 2007.
• [7] Hluchy L., Habala O., Tran V., Ciglan M.: Hydro-meteorological scenarios using advanced data mining and integration. [in:] Fuzzy Systems and Knowledge Discovery, 2009. FSKD ’09. Sixth International Conference on, volume 7, pp. 260–264, aug. 2009.
• [8] Hluch´y L., ˇSeleng M., Habala O., Krammer P.: Mining Environmental Data in Hydrological Scenarios. [in:] M. Li, Q. Liang, L. Wang, Y. Song (Eds.), Seventh International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010, 10-12 August 2010, Yantai, Shandong, China, pp. 1988–2992. IEEE, 2010.
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