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

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          Abstract

          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.

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          Most cited references 22

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          Evaluation: from precision, recall and f-measure to roc, informedness, markedness and correlation

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            Fuzzy logic systems for engineering: a tutorial

             J.M. Mendel (1995)
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              Application of fuzzy sets in soil science: fuzzy logic, fuzzy measurements and fuzzy decisions

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                remi
                REM - International Engineering Journal
                REM, Int. Eng. J.
                Fundação Gorceix (Ouro Preto, MG, Brazil )
                2448-167X
                December 2018
                : 71
                : 4
                : 553-559
                Affiliations
                Criciúma Santa Catarina orgnameAtta Engenharia Brasil emilin@ 123456atta.eng.br
                Criciúma orgnameUniversidade do Extremo Sul Catarinense Brazil kristian@ 123456unesc.net
                Criciúma orgnameUniversidade do Extremo Sul Catarinense Brazil mem@ 123456unesc.net
                Criciúma orgnameUniversidade do Extremo Sul Catarinense Brazil fbs@ 123456unesc.net
                Article
                S2448-167X2018000400553
                10.1590/0370-44672017710155

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 42, Pages: 7
                Product
                Product Information: website

                mining, land reclamation, fuzzy logic, expert system

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