Wengang Zhang - Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience

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The so-called Fourth Paradigm has been boomingly developed during the past two decades, in which large quantities of observational data are available to scientists and engineers. Big data is characterized by the rule of the five Vs: Volume, Variety, Value, Velocity and Veracity. The concept of big data naturally matches well with the features of geoengineering and geoscience. Large-scale, comprehensive, multidirectional and multifield geotechnical data analysis is becoming a trend. On the other hand, soft computing (SC), machine learning (ML), deep learning (DL) and optimization algorithm (OA) provide the ability to learn from data and deliver in-depth insight into geotechnical problems. Researchers use different SC, ML, DL and OA models to solve various problems associated with geoengineering and geoscience. Consequently, there is a need to extend its research with big data research through integrating the use of SC, ML, DL and OA techniques.

This book focuses on the state of the art and application of SC, ML, DL and OA algorithms in geoengineering and geoscience. Various SC, ML, DL and OA approaches are firstly concisely introduced, concerning mainly the easy-to-interpret multivariate adaptive regression splines (MARS) model, supervised learning, unsupervised learning, deep learning and optimization algorithms. Then their representative applications in the geoengineering and geoscience are summarized via VOSviewer demonstration. The authors also provided their own thoughts learnt from these applications as well as work ongoing and future recommendations. This book aims to make a comprehensive summary and provide fundamental guidelines for researchers and engineers in discipline of geoengineering and geoscience or similar research areas on how to integrate and apply SC, ML, DL and OA methods.