Cargando…
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...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5022015/ https://www.ncbi.nlm.nih.gov/pubmed/27689133 http://dx.doi.org/10.1155/2016/9057263 |
_version_ | 1782453439738937344 |
---|---|
author | Tserkovny, Alex |
author_facet | Tserkovny, Alex |
author_sort | Tserkovny, Alex |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-5022015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-50220152016-09-29 Fuzzy Logic for Incidence Geometry Tserkovny, Alex ScientificWorldJournal Research Article 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. Hindawi Publishing Corporation 2016 2016-08-29 /pmc/articles/PMC5022015/ /pubmed/27689133 http://dx.doi.org/10.1155/2016/9057263 Text en Copyright © 2016 Alex Tserkovny. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Tserkovny, Alex Fuzzy Logic for Incidence Geometry |
title | 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_short | Fuzzy Logic for Incidence Geometry |
title_sort | fuzzy logic for incidence geometry |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5022015/ https://www.ncbi.nlm.nih.gov/pubmed/27689133 http://dx.doi.org/10.1155/2016/9057263 |
work_keys_str_mv | AT tserkovnyalex fuzzylogicforincidencegeometry |