Fuzzy Logic for Incidence Geometry

The paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so...

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Main Author: Alex Tserkovny
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2016/9057263
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spelling doaj-add350413c4b4f19a93a064746eeac842020-11-24T21:45:39ZengHindawi LimitedThe Scientific World Journal2356-61401537-744X2016-01-01201610.1155/2016/90572639057263Fuzzy Logic for Incidence GeometryAlex Tserkovny0Dassault Systemes, 175 Wyman Street, Waltham, MA 02451, USAThe paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so forth. Unlike single points that are given in Cartesian coordinates, these geographic entities are extended in space and often loosely defined, but people easily perform spatial reasoning with extended geographic objects “as if they were points.” Unfortunately, up to date, geographic information systems (GIS) miss the capability of geometric reasoning with extended objects. The aim of the paper is to present a mathematical apparatus for approximate geometric reasoning with extended objects that is usable in GIS. In the paper we discuss the fuzzy logic (Aliev and Tserkovny, 2011) as a reasoning system for geometry of extended objects, as well as a basis for fuzzification of the axioms of incidence geometry. The same fuzzy logic was used for fuzzification of Euclid’s first postulate. Fuzzy equivalence relation “extended lines sameness” is introduced. For its approximation we also utilize a fuzzy conditional inference, which is based on proposed fuzzy “degree of indiscernibility” and “discernibility measure” of extended points.http://dx.doi.org/10.1155/2016/9057263
collection DOAJ
language English
format Article
sources DOAJ
author Alex Tserkovny
spellingShingle Alex Tserkovny
Fuzzy Logic for Incidence Geometry
The Scientific World Journal
author_facet Alex Tserkovny
author_sort Alex Tserkovny
title Fuzzy Logic for Incidence Geometry
title_short Fuzzy Logic for Incidence Geometry
title_full Fuzzy Logic for Incidence Geometry
title_fullStr Fuzzy Logic for Incidence Geometry
title_full_unstemmed Fuzzy Logic for Incidence Geometry
title_sort fuzzy logic for incidence geometry
publisher Hindawi Limited
series The Scientific World Journal
issn 2356-6140
1537-744X
publishDate 2016-01-01
description The paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so forth. Unlike single points that are given in Cartesian coordinates, these geographic entities are extended in space and often loosely defined, but people easily perform spatial reasoning with extended geographic objects “as if they were points.” Unfortunately, up to date, geographic information systems (GIS) miss the capability of geometric reasoning with extended objects. The aim of the paper is to present a mathematical apparatus for approximate geometric reasoning with extended objects that is usable in GIS. In the paper we discuss the fuzzy logic (Aliev and Tserkovny, 2011) as a reasoning system for geometry of extended objects, as well as a basis for fuzzification of the axioms of incidence geometry. The same fuzzy logic was used for fuzzification of Euclid’s first postulate. Fuzzy equivalence relation “extended lines sameness” is introduced. For its approximation we also utilize a fuzzy conditional inference, which is based on proposed fuzzy “degree of indiscernibility” and “discernibility measure” of extended points.
url http://dx.doi.org/10.1155/2016/9057263
work_keys_str_mv AT alextserkovny fuzzylogicforincidencegeometry
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