Machine Learning Applications
Machine learning is increasingly transforming geology and earth sciences by enhancing data analysis and predictive modeling. In geology, it aids in mineral exploration through pattern recognition in geological data, optimizing drilling locations based on predictive algorithms, and identifying geological hazards like landslides and earthquakes using sensor data. Earth science benefits from machine learning in climate modeling, analyzing satellite imagery for environmental monitoring, and predicting natural disasters such as hurricanes and tsunamis. These applications leverage machine learning's ability to handle vast datasets and complex relationships, providing valuable insights for both research and practical applications in geology and earth sciences.
Myint Win Bo
Toronto Metropolitan University , Canada
Leonid Anisimov
Volgograd State University, Russian Federation
Shozo Yanagida
Osaka University, Japan
Martina Gaglioti
LIPU, Italy
Maria Vicenta Esteller Alberich
Universidad Autónoma del Estado de México, Mexico
Oscar Andres Cuanalo Campos
Universidad Popular Autónoma del Estado de Puebla, Mexico
Arun K Shandilya
Dr HSG University Sagar, India
Title : Geotechnical ground investigation
Myint Win Bo, Toronto Metropolitan University , Canada
Title : Simultaneous Global Climate Change "Heat Waves" and microwave and radio-wave from Solar Flares
Shozo Yanagida, Osaka University, Japan
Title : How subsurface waters record the earth’s history
Leonid Anisimov, Volgograd State University, Russian Federation
Title : Landslides.Rainfall one of the main triggering factors in the mountainous regions of Puebla, Mexico.
Oscar Andres Cuanalo Campos, Universidad Popular Autónoma del Estado de Puebla, Mexico
Title : Geo Education exploratory learning sessions on field and underwater
Martina Gaglioti, LIPU, Italy
Title : Linking between color and element concentration for Fluorite: An optical spectroscopic approach
Ali Almohammed, Pandit Deendayal Energy University, India