Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience (PDF)
(Sprache: Englisch)
This book summarizes the application of soft computing techniques, machine learning approaches, deep learning algorithms and optimization techniques in geoengineering including tunnelling, excavation, pipelines, etc. and geoscience including the geohazards,...
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This book summarizes the application of soft computing techniques, machine learning approaches, deep learning algorithms and optimization techniques in geoengineering including tunnelling, excavation, pipelines, etc. and geoscience including the geohazards, rock and soil properties, etc. The book features state-of-the-art studies on use of SC,ML,DL and optimizations in Geoengineering and Geoscience.
Considering these points and understanding, this book will be compiled with highly focussed chapters that will discuss the application of SC,ML,DL and optimizations in Geoengineering and Geoscience.
Target audience: (1) Students of UG, PG, and Research Scholars: Several applications of SC,ML,DL and optimizations in Geoengineering and Geoscience can help students to enhance their knowledge in this domain. (2) Industry Personnel and Practitioner: Practitioners from different fields can be able to implement standard and advanced SC,ML,DL and optimizations for solving critical problems of civil engineering.
Autoren-Porträt von Wengang Zhang, Yanmei Zhang, Xin Gu, Chongzhi Wu, Liang Han
ZHANG Wengang PhD, Professor, Associate Chair at School of Civil Engineering, Chongqing University. He got his PhD at Nanyang Technological University (NTU), Singapore in 2014. AWARDS
Computers and Geotechnics 2019 Sloan Outstanding Paper Award
Chongqing Science and Technology Award, First Prize in Natural Science (5/5)
Overseas High-level Talents (Young Thousand Talented Professor)
Leader of Academia & Technology in Chongqing (The 3rd Batch)
Bibliographische Angaben
- Autoren: Wengang Zhang , Yanmei Zhang , Xin Gu , Chongzhi Wu , Liang Han
- 2021, 1st ed. 2022, 138 Seiten, Englisch
- Verlag: Springer Nature Singapore
- ISBN-10: 9811668353
- ISBN-13: 9789811668357
- Erscheinungsdatum: 12.10.2021
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Dateiformat: PDF
- Größe: 4.95 MB
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Sprache:
Englisch
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