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Fuzzy modeling with spatial information for geographic problems

The capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our...

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Detalles Bibliográficos
Autores principales: Petry, Frederick E, Robinson, Vincent B, Cobb, Maria A
Lenguaje:eng
Publicado: Springer 2005
Materias:
XX
Acceso en línea:http://cds.cern.ch/record/2283261
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author Petry, Frederick E
Robinson, Vincent B
Cobb, Maria A
author_facet Petry, Frederick E
Robinson, Vincent B
Cobb, Maria A
author_sort Petry, Frederick E
collection CERN
description The capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our need to model and manipulate our knowledge of the geophysical world, using compatible representations, is also rapidly increasing. In response to this one fundamental issue of great concern in modern geographical research is how to most effectively capture the physical world around us in systems like geographical information systems (GIS). Making this task even more challenging is the fact that uncertainty plays a pervasive role in the representation, analysis and use of geospatial information. The types of uncertainty that appear in geospatial information systems are not the just simple randomness of observation, as in weather data, but are manifested in many other forms including imprecision, incompleteness and granularization. Describing the uncertainty of the boundaries of deserts and mountains clearly require different tools than those provided by probability theory. The multiplicity of modalities of uncertainty appearing in GIS requires a variety of formalisms to model these uncertainties. In light of this it is natural that fuzzy set theory has become a topic of intensive interest in many areas of geographical research and applications This volume, Fuzzy Modeling with Spatial Information for Geographic Problems, provides many stimulating examples of advances in geographical research based on approaches using fuzzy sets and related technologies.
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spelling cern-22832612021-04-21T19:04:34Zhttp://cds.cern.ch/record/2283261engPetry, Frederick ERobinson, Vincent BCobb, Maria AFuzzy modeling with spatial information for geographic problemsXXThe capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our need to model and manipulate our knowledge of the geophysical world, using compatible representations, is also rapidly increasing. In response to this one fundamental issue of great concern in modern geographical research is how to most effectively capture the physical world around us in systems like geographical information systems (GIS). Making this task even more challenging is the fact that uncertainty plays a pervasive role in the representation, analysis and use of geospatial information. The types of uncertainty that appear in geospatial information systems are not the just simple randomness of observation, as in weather data, but are manifested in many other forms including imprecision, incompleteness and granularization. Describing the uncertainty of the boundaries of deserts and mountains clearly require different tools than those provided by probability theory. The multiplicity of modalities of uncertainty appearing in GIS requires a variety of formalisms to model these uncertainties. In light of this it is natural that fuzzy set theory has become a topic of intensive interest in many areas of geographical research and applications This volume, Fuzzy Modeling with Spatial Information for Geographic Problems, provides many stimulating examples of advances in geographical research based on approaches using fuzzy sets and related technologies.Springeroai:cds.cern.ch:22832612005
spellingShingle XX
Petry, Frederick E
Robinson, Vincent B
Cobb, Maria A
Fuzzy modeling with spatial information for geographic problems
title Fuzzy modeling with spatial information for geographic problems
title_full Fuzzy modeling with spatial information for geographic problems
title_fullStr Fuzzy modeling with spatial information for geographic problems
title_full_unstemmed Fuzzy modeling with spatial information for geographic problems
title_short Fuzzy modeling with spatial information for geographic problems
title_sort fuzzy modeling with spatial information for geographic problems
topic XX
url http://cds.cern.ch/record/2283261
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