Intelligent Analysis of Hurricane Data over GIS Applications Intelligent Analysis of Hurricane Data over GIS Applications

Intelligent Analysis of Hurricane Data over GIS Applications

    • ‏23٫99 US$
    • ‏23٫99 US$

وصف الناشر

Geographical Information Systems (GIS) research area have been evolving with time. Those systems have become useful beyond spatial and geographic information representation and computer aided analysis using maps.

Some of the most important fields of application for GIS are fleet control, tourism analysis and Meteorological analysis. For the last mentioned field, advisory and prediction models should be enhanced aiming the avoidance of critical damage associated to Hurricanes. Intelligent systems have become the optimal solution when decision-making situations are extreme and advanced reasoning is expected.

Existing models involve high mathematical analysis, which is complex for humans and also sometimes computational costs have to be considered. There are some artificial intelligence fields that are exploring the possibility of making inference about existing data, enriching the information and enhancing the obtained results. In the present work we propose a hybrid GIS which includes some behavioral aspects of intelligent systems for Hurricane analysis.

النوع
علم وطبيعة
تاريخ النشر
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١٥ نوفمبر
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
GRIN Verlag
البائع
Open Publishing GmbH
الحجم
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ك.ب.
Research Trends in Geographic Information Science Research Trends in Geographic Information Science
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Metaheuristic Clustering Metaheuristic Clustering
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Information Fusion and Geographic Information Systems (IF&GIS' 2015) Information Fusion and Geographic Information Systems (IF&GIS' 2015)
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The European Information Society The European Information Society
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Geospatial Thinking Geospatial Thinking
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Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017) Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017)
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