The complexity of geochemical patterns in the surficial media makes it necessary to consider
the uncertainty in the process of identifying geochemical anomalies. The existence of …

Correlation coefficients (CC) are statistical tools that measure how strong a relationship is
between two variables. In geochemical studies, these variables could be different elements' …

Fusion and analysis of thematic information layers using machine learning algorithms
provide an important step toward achieving accurate mineral potential maps in the …

Prediction of geochemical concentration values is essential in mineral exploration as it plays
a principal role in the economic section. In this paper, four regression machine learning (ML) …

Traditional time series prediction methods have shown their outstanding capabilities in time
series prediction. However, due to essential differences in volatility characteristics among …

Geochemical anomaly patterns for metal exploration targeting usually reveal non-stationarity
due mainly to the non-linear synthesis of ore-forming processes. The spectrum–area (S–A) …

Prediction of elemental concentrations is essential in mineral exploration as it plays a vital
role in detailed exploration. New machine learning (ML) methods such as hybrid models are …

Groundwater potential delineation in the Akka basin, southwest Morocco, has been
determined through the combination of geospatial techniques and geological data. The …

Water scarcity affects all continents, with approximately 1.2 billion people living in areas
where water is physically lacking. This scarcity is more accentuated in countries with an arid …

In geologically and lithologically complex areas, distinguishing weak geochemical
anomalies from background and defining a valid threshold value are central issues in …