An interval fuzzy model for magnetic biomonitoring using the specie Tillandsia recurvata L

Studies of magnetic monitoring for assessing air pollution have been proposed as alternative and complimentary of chemical methods. Such magnetic studies provide measurements at low cost and relative promptness. In this work, we present and apply a methodology to build an interval fuzzy model, which...

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Detalles Bibliográficos
Publicado: 2015
Materias:
Biomonitoring, Fuzzy c-means clustering
Magnetic parameters
Model
Pollution
Chemical analysis
Magnetic materials
Minerals
Models
Chemical variables
Fuzzy C means clustering
Interval fuzzy model
Magnetic concentration
Magnetic monitoring
Magnetic studies
Pollution load indices
Magnetism
atmospheric pollution
biomonitoring
fuzzy mathematics
index method
magnetic property
monocotyledon
numerical model
pollution monitoring
Dominican Republic
Santiago Rodriguez
Tillandsia recurvata
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_1470160X_v54_n_p238_Chaparro
http://hdl.handle.net/20.500.12110/paper_1470160X_v54_n_p238_Chaparro
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_1470160X_v54_n_p238_Chaparro
record_format dspace
spelling paper:paper_1470160X_v54_n_p238_Chaparro2023-06-08T16:17:00Z An interval fuzzy model for magnetic biomonitoring using the specie Tillandsia recurvata L Biomonitoring, Fuzzy c-means clustering Magnetic parameters Model Pollution Chemical analysis Magnetic materials Minerals Models Pollution Chemical variables Fuzzy C means clustering Interval fuzzy model Magnetic concentration Magnetic monitoring Magnetic parameters Magnetic studies Pollution load indices Magnetism atmospheric pollution biomonitoring fuzzy mathematics index method magnetic property monocotyledon numerical model pollution monitoring Dominican Republic Santiago Rodriguez Tillandsia recurvata Studies of magnetic monitoring for assessing air pollution have been proposed as alternative and complimentary of chemical methods. Such magnetic studies provide measurements at low cost and relative promptness. In this work, we present and apply a methodology to build an interval fuzzy model, which calculates the Tomlinson pollution load index (PLI). The input variables for the model are magnetic parameters relative to magnetic concentration, grain size and mineralogy. The model aims to two purposes, on one hand, to calculate the values of PLI only using magnetic variables and, on the other hand, to analyze the relationship between magnetic and chemical variables. The studied dataset was obtained from measurements of the biomonitor Tillandsia recurvata L. in a Mexican urban area (Santiago de Querétaro). The best model was selected from a total of about half a million possible models using a fitness measure (RIF). The model yields a satisfactory approximation of the PLI data and it was concluded that PLI increases with relation to: an increase in concentration of magnetic materials, an additional contribution to the magnetic signal of paramagnetic materials, and an increase in size of magnetic grains. © 2015 Elsevier Ltd. All rights reserved. 2015 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_1470160X_v54_n_p238_Chaparro http://hdl.handle.net/20.500.12110/paper_1470160X_v54_n_p238_Chaparro
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Biomonitoring, Fuzzy c-means clustering
Magnetic parameters
Model
Pollution
Chemical analysis
Magnetic materials
Minerals
Models
Pollution
Chemical variables
Fuzzy C means clustering
Interval fuzzy model
Magnetic concentration
Magnetic monitoring
Magnetic parameters
Magnetic studies
Pollution load indices
Magnetism
atmospheric pollution
biomonitoring
fuzzy mathematics
index method
magnetic property
monocotyledon
numerical model
pollution monitoring
Dominican Republic
Santiago Rodriguez
Tillandsia recurvata
spellingShingle Biomonitoring, Fuzzy c-means clustering
Magnetic parameters
Model
Pollution
Chemical analysis
Magnetic materials
Minerals
Models
Pollution
Chemical variables
Fuzzy C means clustering
Interval fuzzy model
Magnetic concentration
Magnetic monitoring
Magnetic parameters
Magnetic studies
Pollution load indices
Magnetism
atmospheric pollution
biomonitoring
fuzzy mathematics
index method
magnetic property
monocotyledon
numerical model
pollution monitoring
Dominican Republic
Santiago Rodriguez
Tillandsia recurvata
An interval fuzzy model for magnetic biomonitoring using the specie Tillandsia recurvata L
topic_facet Biomonitoring, Fuzzy c-means clustering
Magnetic parameters
Model
Pollution
Chemical analysis
Magnetic materials
Minerals
Models
Pollution
Chemical variables
Fuzzy C means clustering
Interval fuzzy model
Magnetic concentration
Magnetic monitoring
Magnetic parameters
Magnetic studies
Pollution load indices
Magnetism
atmospheric pollution
biomonitoring
fuzzy mathematics
index method
magnetic property
monocotyledon
numerical model
pollution monitoring
Dominican Republic
Santiago Rodriguez
Tillandsia recurvata
description Studies of magnetic monitoring for assessing air pollution have been proposed as alternative and complimentary of chemical methods. Such magnetic studies provide measurements at low cost and relative promptness. In this work, we present and apply a methodology to build an interval fuzzy model, which calculates the Tomlinson pollution load index (PLI). The input variables for the model are magnetic parameters relative to magnetic concentration, grain size and mineralogy. The model aims to two purposes, on one hand, to calculate the values of PLI only using magnetic variables and, on the other hand, to analyze the relationship between magnetic and chemical variables. The studied dataset was obtained from measurements of the biomonitor Tillandsia recurvata L. in a Mexican urban area (Santiago de Querétaro). The best model was selected from a total of about half a million possible models using a fitness measure (RIF). The model yields a satisfactory approximation of the PLI data and it was concluded that PLI increases with relation to: an increase in concentration of magnetic materials, an additional contribution to the magnetic signal of paramagnetic materials, and an increase in size of magnetic grains. © 2015 Elsevier Ltd. All rights reserved.
title An interval fuzzy model for magnetic biomonitoring using the specie Tillandsia recurvata L
title_short An interval fuzzy model for magnetic biomonitoring using the specie Tillandsia recurvata L
title_full An interval fuzzy model for magnetic biomonitoring using the specie Tillandsia recurvata L
title_fullStr An interval fuzzy model for magnetic biomonitoring using the specie Tillandsia recurvata L
title_full_unstemmed An interval fuzzy model for magnetic biomonitoring using the specie Tillandsia recurvata L
title_sort interval fuzzy model for magnetic biomonitoring using the specie tillandsia recurvata l
publishDate 2015
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_1470160X_v54_n_p238_Chaparro
http://hdl.handle.net/20.500.12110/paper_1470160X_v54_n_p238_Chaparro
_version_ 1768541909307883520

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