Merisandra Côrtes de Mattos Garcia

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

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-TakesAll 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.

Algoritmos de Inteligência de Enxames por Colônia de Formigas na Análise de Indicadores Ambientais de Bacias Hidrográficas

Resumo—Tecnologias atuais de armazenamento permitem gerar grandes bases de dados, as quais podem possuir informações desconhecidas. Dessa forma, são necessárias tecnologias voltadas a explorar essas bases, tendo-se o data mining como uma dessas tecnologias, que utiliza algoritmos para extrair conhecimento e padrões presentes nos dados. Este artigo demonstra a aplicação do Standard Ant Clustering Algorithm, Ant Based Clustering e Adaptative Ant-Clustering Algorithm, pertencentes à tarefa de agrupamento, para análise de dados referente aos indicadores do monitoramento de bacias hidrográficas da região carbonífera do Sul de Santa Catarina. A tarefa de agrupamento objetiva reunir uma base de dados em grupos de dados semelhantes, sendo que os algoritmos aplicados nessa pesquisa simulam o comportamento da organização de cemitérios observados em espécies de formigas.