A fuzzy logic-based expert system for substrate selection for soil construction in land reclamation

Abstract The mining industry can be one of the most impacting human activities. In the southern region of Santa Catarina (Brazil), open pit coal mining has left an extensive environmental impact. Since there was no topsoil in the abandoned open pit sites, it is necessary to provide a substrate for v...

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Main Authors: Fernando Basquiroto de Souza, Émilin de Jesus Casagrande de Souza, Merisandra Côrtes de Mattos Garcia, Kristian Madeira
Format: Article
Language:English
Published: Fundação Gorceix
Series:REM: International Engineering Journal
Subjects:
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2018000400553&lng=en&tlng=en
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spelling doaj-3b5ece25d684480d8c1c1815ddfefd4c2020-11-24T23:38:47ZengFundação GorceixREM: International Engineering Journal2448-167X71455355910.1590/0370-44672017710155S2448-167X2018000400553A fuzzy logic-based expert system for substrate selection for soil construction in land reclamationFernando Basquiroto de SouzaÉmilin de Jesus Casagrande de SouzaMerisandra Côrtes de Mattos GarciaKristian MadeiraAbstract The mining industry can be one of the most impacting human activities. In the southern region of Santa Catarina (Brazil), open pit coal mining has left an extensive environmental impact. Since there was no topsoil in the abandoned open pit sites, it is necessary to provide a substrate for vegetation growth. However, the selection of the best substrate between multiple options is difficult. Thus, a fuzzy logic-based model is proposed. The proposed model was compared to reference models and to experts’ knowledge. Statistical analysis and validation were carried out with a correlation coefficient, a Kappa coefficient, along with the Accuracy, Precision, Sensibility Specificity, F-Score and Mathews correlation coefficients. The data set used to assess the proposed model presented a wide range of data, but for values such as aluminum saturation, higher values were common. The fuzzy logic-based expert system presented better results when assessing the behavior of the defuzzified output values with the crisp input values. The fuzzy model also followed the trend of the reference models (with R2 between 0.3639 and 0.5250). The comparison to the experts’ opinion demonstrated that agreement comes easily with extreme values (such as not suitable and suitable). However, using a Winner-Takes-All approach, the proposed fuzzy model had high scores for suitable soils for land reclamation’s soil construction. The proposed model can be used to define the best substrate for land reclamation. Some improvements, such as different parameters and increases in the number of interviews rounds, should be also tested.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2018000400553&lng=en&tlng=enfuzzy logicexpert systemminingland reclamation
collection DOAJ
language English
format Article
sources DOAJ
author Fernando Basquiroto de Souza
Émilin de Jesus Casagrande de Souza
Merisandra Côrtes de Mattos Garcia
Kristian Madeira
spellingShingle Fernando Basquiroto de Souza
Émilin de Jesus Casagrande de Souza
Merisandra Côrtes de Mattos Garcia
Kristian Madeira
A fuzzy logic-based expert system for substrate selection for soil construction in land reclamation
REM: International Engineering Journal
fuzzy logic
expert system
mining
land reclamation
author_facet Fernando Basquiroto de Souza
Émilin de Jesus Casagrande de Souza
Merisandra Côrtes de Mattos Garcia
Kristian Madeira
author_sort Fernando Basquiroto de Souza
title A fuzzy logic-based expert system for substrate selection for soil construction in land reclamation
title_short A fuzzy logic-based expert system for substrate selection for soil construction in land reclamation
title_full A fuzzy logic-based expert system for substrate selection for soil construction in land reclamation
title_fullStr A fuzzy logic-based expert system for substrate selection for soil construction in land reclamation
title_full_unstemmed A fuzzy logic-based expert system for substrate selection for soil construction in land reclamation
title_sort fuzzy logic-based expert system for substrate selection for soil construction in land reclamation
publisher Fundação Gorceix
series REM: International Engineering Journal
issn 2448-167X
description Abstract The mining industry can be one of the most impacting human activities. In the southern region of Santa Catarina (Brazil), open pit coal mining has left an extensive environmental impact. Since there was no topsoil in the abandoned open pit sites, it is necessary to provide a substrate for vegetation growth. However, the selection of the best substrate between multiple options is difficult. Thus, a fuzzy logic-based model is proposed. The proposed model was compared to reference models and to experts’ knowledge. Statistical analysis and validation were carried out with a correlation coefficient, a Kappa coefficient, along with the Accuracy, Precision, Sensibility Specificity, F-Score and Mathews correlation coefficients. The data set used to assess the proposed model presented a wide range of data, but for values such as aluminum saturation, higher values were common. The fuzzy logic-based expert system presented better results when assessing the behavior of the defuzzified output values with the crisp input values. The fuzzy model also followed the trend of the reference models (with R2 between 0.3639 and 0.5250). The comparison to the experts’ opinion demonstrated that agreement comes easily with extreme values (such as not suitable and suitable). However, using a Winner-Takes-All approach, the proposed fuzzy model had high scores for suitable soils for land reclamation’s soil construction. The proposed model can be used to define the best substrate for land reclamation. Some improvements, such as different parameters and increases in the number of interviews rounds, should be also tested.
topic fuzzy logic
expert system
mining
land reclamation
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2448-167X2018000400553&lng=en&tlng=en
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