Failure risk of brazilian tailings dams: a data mining approach

Abstract This paper proposes the use of a hybrid method that combines Biased Random Key Genetic Algorithm (BRKGA) with local search heuristic to separate Brazilian tailing dam data into groups. The goal was identifying dams similar Fundao and B1 failed dams. groups were created by solving clustering problem BRKGA. consists in separating set objects such members each group are other. composed 427 dams, actual 425 Register Tailing Dams two from last years. Computational experiments considering real available presented demonstrate efficacy proposed producing feasible solutions. Thus, it is expected good results can be applied identification tailings risk potentials, assisting these