A Primer on Machine Learning Applications in Civil Engineering
CRC Press (Verlag)
978-1-138-32339-1 (ISBN)
Machine learning has undergone rapid growth in diversification and practicality, and the repertoire of techniques has evolved and expanded. The aim of this book is to provide a broad overview of the available machine-learning techniques that can be utilized for solving civil engineering problems. The fundamentals of both theoretical and practical aspects are discussed in the domains of water resources/hydrological modeling, geotechnical engineering, construction engineering and management, and coastal/marine engineering. Complex civil engineering problems such as drought forecasting, river flow forecasting, modeling evaporation, estimation of dew point temperature, modeling compressive strength of concrete, ground water level forecasting, and significant wave height forecasting are also included.
Features
Exclusive information on machine learning and data analytics applications with respect to civil engineering
Includes many machine learning techniques in numerous civil engineering disciplines
Provides ideas on how and where to apply machine learning techniques for problem solving
Covers water resources and hydrological modeling, geotechnical engineering, construction engineering and management, coastal and marine engineering, and geographical information systems
Includes MATLAB® exercises
Paresh Chandra Deka earned a bachelor’s in civil engineering at the National Institute of Technology, Silchar, Assam, India, and a PhD at the Indian Institute of Technology, Guwahati, specializing in hydrological modeling. Dr. Deka served on the faculty at the School of Postgraduate Studies at Arbaminch University, Ethiopia from 2005 to 2008 and as visiting faculty in 2012 at the Asian Institute of Technology, Bangkok, Thailand. He has supervised 10 PhD scholars as well as 5 current PhD scholars. He has supervised 40 master’s theses as well as 4 current master’s students. His research area is soft computing applications in water resources engineering and management. Dr. Deka has published 4 books, 5 book chapters, and more than 40 international journal papers. He is a visiting faculty member doing short-term research interaction at Purdue University, Indiana. With more than 28 years of teaching experience, he is currently a professor in the Department of Applied Mechanics and Hydraulics at the National Institute of Technology, Surathkal, Karnataka, India.
1. Introduction 2. Artificial Neural Networks 3. Fuzzy Logic 4. Support Vector Machine 5. Genetic Algorithm (GA) 6. Hybrid Systems 7. Data Statistics and Analytics 8. Applications in the Civil Engineering Domain 9. Conclusion and Future Scope of Work
| Erscheinungsdatum | 15.11.2019 |
|---|---|
| Zusatzinfo | 56 Tables, black and white; 67 Illustrations, color; 46 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 1180 g |
| Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-138-32339-X / 113832339X |
| ISBN-13 | 978-1-138-32339-1 / 9781138323391 |
| Zustand | Neuware |
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