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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 references22

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          The Measurement of Observer Agreement for Categorical Data

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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

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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
                [2] Criciúma Santa Catarina orgnameAtta Engenharia Brasil emilin@ 123456atta.eng.br
                [4] Criciúma orgnameUniversidade do Extremo Sul Catarinense Brazil kristian@ 123456unesc.net
                [3] Criciúma orgnameUniversidade do Extremo Sul Catarinense Brazil mem@ 123456unesc.net
                [1] Criciúma orgnameUniversidade do Extremo Sul Catarinense Brazil fbs@ 123456unesc.net
                Article
                S2448-167X2018000400553
                10.1590/0370-44672017710155
                c039faa6-24cc-4b43-a96c-37e83ee681d7

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

                History
                : 02 May 2018
                : 30 June 2017
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 42, Pages: 7
                Product

                SciELO Brazil


                mining,land reclamation,fuzzy logic,expert system
                mining, land reclamation, fuzzy logic, expert system

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