Evaluation of predictive models for the optimization of the cost of unit operations in artisanal underground mining

HIGHLIGHTS

• What: The aim of this study is to evaluate and optimize the costs of unit operations in artisanal underground mining through the application of predictive models based on machine learning. The neural_network used in this research work has the following structure: an input layer with 16 neurons, followed by dense hidden layers with sizes of 20, 30, 30, 30, 20 and 10 neurons, respectively, and an output layer with 1 neuron. As the model moves down the tree, successive decision rules are applied until it reaches a leaf, which provides the final prediction. This figure details the . . .
  

   

  

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