An interval fuzzy model for magnetic monitoring: estimation of a pollution index
In this contribution, a methodology is reported in order to build an interval fuzzy model for the pollution index PLI (a composite index using relevant heavy metal concentration) with magnetic parameters as input variables. In general, modelling based on fuzzy set theory is designed to mimic how the...
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ftconicet:oai:ri.conicet.gov.ar:11336/197127 2023-10-09T21:47:13+02:00 An interval fuzzy model for magnetic monitoring: estimation of a pollution index Chaparro, Mauro Alejandro Eduardo Chaparro, Marcos Adrián Eduardo Sinito, Ana Maria application/pdf http://hdl.handle.net/11336/197127 eng eng Springer info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s12665-011-1387-z info:eu-repo/semantics/altIdentifier/doi/10.1007/s12665-011-1387-z http://hdl.handle.net/11336/197127 Chaparro, Mauro Alejandro Eduardo; Chaparro, Marcos Adrián Eduardo; Sinito, Ana Maria; An interval fuzzy model for magnetic monitoring: estimation of a pollution index; Springer; Environmental Earth Sciences; 66; 7-2012; 1477-1485 1866-6280 CONICET Digital CONICET info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Interval fuzzy model Fuzzy c -means clustering Magnetic monitoring Pollution https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 info:eu-repo/semantics/article info:ar-repo/semantics/artículo info:eu-repo/semantics/publishedVersion ftconicet https://doi.org/10.1007/s12665-011-1387-z 2023-09-24T19:09:06Z In this contribution, a methodology is reported in order to build an interval fuzzy model for the pollution index PLI (a composite index using relevant heavy metal concentration) with magnetic parameters as input variables. In general, modelling based on fuzzy set theory is designed to mimic how the human brain tends to classify imprecise information or data. The ??interval fuzzy model?? reported here, based on fuzzy logic and arithmetic of fuzzy numbers, calculates an ??estimation interval?? and seems to be an adequate mathematical tool for this nonlinear problem. For this model, fuzzy c-means clustering is used to partition data, hence the membership functions and rules are built. In addition, interval arithmetic is used to obtain the fuzzy intervals. The studied sets are different examples of pollution by different anthropogenic sources, in two different study areas: (a) soil samples collected in Antarctica and (b) road-deposited sediments collected in Argentina. The datasets comprise magnetic and chemical variables, and for both cases, relevant variables were selected: magnetic concentration-dependent variables, magnetic features-dependent variables and one chemical variable. The model output gives an estimation interval; its width depends on the data density, for the measured values. The results show not only satisfactory agreement between the estimation interval and data, but also provide valued information from the rules analysis that allows understanding the magnetic behaviour of the studied variables under different conditions. Fil: Chaparro, Mauro Alejandro Eduardo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina Fil: Chaparro, Marcos Adrián Eduardo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de ... Article in Journal/Newspaper Antarc* Antarctica CONICET Digital (Consejo Nacional de Investigaciones Científicas y Técnicas) Argentina Marcos ENVELOPE(-61.833,-61.833,-64.500,-64.500) Environmental Earth Sciences 66 5 1477 1485 |
institution |
Open Polar |
collection |
CONICET Digital (Consejo Nacional de Investigaciones Científicas y Técnicas) |
op_collection_id |
ftconicet |
language |
English |
topic |
Interval fuzzy model Fuzzy c -means clustering Magnetic monitoring Pollution https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 |
spellingShingle |
Interval fuzzy model Fuzzy c -means clustering Magnetic monitoring Pollution https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 Chaparro, Mauro Alejandro Eduardo Chaparro, Marcos Adrián Eduardo Sinito, Ana Maria An interval fuzzy model for magnetic monitoring: estimation of a pollution index |
topic_facet |
Interval fuzzy model Fuzzy c -means clustering Magnetic monitoring Pollution https://purl.org/becyt/ford/1.1 https://purl.org/becyt/ford/1 |
description |
In this contribution, a methodology is reported in order to build an interval fuzzy model for the pollution index PLI (a composite index using relevant heavy metal concentration) with magnetic parameters as input variables. In general, modelling based on fuzzy set theory is designed to mimic how the human brain tends to classify imprecise information or data. The ??interval fuzzy model?? reported here, based on fuzzy logic and arithmetic of fuzzy numbers, calculates an ??estimation interval?? and seems to be an adequate mathematical tool for this nonlinear problem. For this model, fuzzy c-means clustering is used to partition data, hence the membership functions and rules are built. In addition, interval arithmetic is used to obtain the fuzzy intervals. The studied sets are different examples of pollution by different anthropogenic sources, in two different study areas: (a) soil samples collected in Antarctica and (b) road-deposited sediments collected in Argentina. The datasets comprise magnetic and chemical variables, and for both cases, relevant variables were selected: magnetic concentration-dependent variables, magnetic features-dependent variables and one chemical variable. The model output gives an estimation interval; its width depends on the data density, for the measured values. The results show not only satisfactory agreement between the estimation interval and data, but also provide valued information from the rules analysis that allows understanding the magnetic behaviour of the studied variables under different conditions. Fil: Chaparro, Mauro Alejandro Eduardo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto Multidisciplinario de Ecosistemas y Desarrollo Sustentable; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina Fil: Chaparro, Marcos Adrián Eduardo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de ... |
format |
Article in Journal/Newspaper |
author |
Chaparro, Mauro Alejandro Eduardo Chaparro, Marcos Adrián Eduardo Sinito, Ana Maria |
author_facet |
Chaparro, Mauro Alejandro Eduardo Chaparro, Marcos Adrián Eduardo Sinito, Ana Maria |
author_sort |
Chaparro, Mauro Alejandro Eduardo |
title |
An interval fuzzy model for magnetic monitoring: estimation of a pollution index |
title_short |
An interval fuzzy model for magnetic monitoring: estimation of a pollution index |
title_full |
An interval fuzzy model for magnetic monitoring: estimation of a pollution index |
title_fullStr |
An interval fuzzy model for magnetic monitoring: estimation of a pollution index |
title_full_unstemmed |
An interval fuzzy model for magnetic monitoring: estimation of a pollution index |
title_sort |
interval fuzzy model for magnetic monitoring: estimation of a pollution index |
publisher |
Springer |
url |
http://hdl.handle.net/11336/197127 |
long_lat |
ENVELOPE(-61.833,-61.833,-64.500,-64.500) |
geographic |
Argentina Marcos |
geographic_facet |
Argentina Marcos |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007/s12665-011-1387-z info:eu-repo/semantics/altIdentifier/doi/10.1007/s12665-011-1387-z http://hdl.handle.net/11336/197127 Chaparro, Mauro Alejandro Eduardo; Chaparro, Marcos Adrián Eduardo; Sinito, Ana Maria; An interval fuzzy model for magnetic monitoring: estimation of a pollution index; Springer; Environmental Earth Sciences; 66; 7-2012; 1477-1485 1866-6280 CONICET Digital CONICET |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
op_doi |
https://doi.org/10.1007/s12665-011-1387-z |
container_title |
Environmental Earth Sciences |
container_volume |
66 |
container_issue |
5 |
container_start_page |
1477 |
op_container_end_page |
1485 |
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1779310153348153344 |