New Advances In Geochemical Modeling And Mineral Prospectivity Mapping

This Special Issue focuses on original research and new advances in geochemical anomaly modeling (GAM) and mineral prospectivity mapping (MPM). It discusses the application of machine learning and deep learning algorithms, fractal/multifractal approaches, and clustering algorithms for GAM and MPM. It also highlights the challenges of applying supervised machine learning algorithms, unsupervised clustering and fractal/multifractal techniques for GAM and MPM. Lastly, it introduces several metaheuristic optimization algorithms that can be used to support machine learning, deep learning and clustering techniques for discovering faster and more accurate solutions.