Predicción de la ocurrencia de depósitos minerales tipo pórfido usando técnicas de aprendizaje automático

Abstract

Mineral prospectivity mapping is used to delimit potential sources of raw materials. This thesis investigates machine-learning approaches for predicting porphyry-type mineral occurrences, including artificial neural networks, random forests, and support vector machines, as alternatives to methods that require categorical transformations, linear assumptions, or expert-assigned weights.

Authors

1. Ana Gabriela Mantilla Dulcey

Citation

@thesis{Dulcey2023Prediccin,
  title = {Predicción de la ocurrencia de depósitos minerales tipo pórfido usando técnicas de aprendizaje automático},
  author = {Ana Gabriela Mantilla Dulcey},
  year = {2023},
  journal = {Universidad Industrial de Santander},
  url = {https://noesis.uis.edu.co/server/api/core/bitstreams/176d56cf-434b-4d01-9ed0-fedf3137b577/content},
  note = {Metadata last verified 2026-07-29}
}

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