Thus, we review the basic concept of the ML and describe more advanced methods, known as deep-learning algorithms. Then, the application of such methods to various problems in porous media and geoscience, such as hydrological modeling, fluid flow in porous media, and (sub)surface ...
Physics-Based and Statistical ApproachesApplication of Geoscience Methods in Landscape ArchaeologyApplication of Speleothems in Paleoclimate and Paleoenvironmental ReconstructionApplication of Thermochronology to Sedimentary BasinsApplications of Artificial Intelligence and Machine Learning in Geotechnical EngineeringApplicati...
This review gives an overview of the development of machine learning in geoscience. A thorough analysis of the co-developments of machine learning applications throughout the last 70 years relates the recent enthusiasm for machine learning to developments in geoscience. I explore the shift of kriging...
nonparametric regres- sion or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The...
Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. In this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the ...
Annette L. Walkerd a.Hanson Center for Space Science, University of Texas at Dallas, Richardson, TX 75080, USA; b.Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, USA; c.BEACON Center for the Study of Evolution in Action, Michigan State Un...
F. Leung. Big data and machine learning in geoscience and geoengineering: Introduction[J]. Geoscience Frontiers, 2021, 12(1): 327-329. DOI: 10.1016/j.gsf.2020.05.006 Citation: Wengang Zhang, Wengang Zhang, Jianye Ching, Andy Y. F. Leung. Big data and machine learning in geoscience ...
For discriminating between tsunami and non-tsunami sediments, the proposed method has a very large advantage over the previous multivariate methods because it utilises labelled (supervised) data. In addition, the proposed method can obtain the most important combination of elements using an exhaustive ...
Non-parametric machine learning methods for interpolation of spatially varying non-stationary and non-Gaussian geotechnical properties[J]. Geoscience Frontiers, 2021, 12(1): 339-350. DOI: 10.1016/j.gsf.2020.01.011 Citation: Chao Shi, Yu Wang. Non-parametric machine learning methods for ...
Recently, using machine learning methods in geoscience studies has been increasing in various applications, including mapping land-cover types and monitoring land usage. Some work has been carried out in the field of identifying and classifying lithologies of valuable minerals [56]. Digital image cl...