A Primer on Machine Learning Applications in Civil Engineering - Deka, Paresh Chandra
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Présentation A Primer On Machine Learning Applications In Civil Engineering Format Relié
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Résumé :
This book provides a broad overview of the available machine learning techniques for solving civil engineering problems including drought forecasting, river flow forecasting, precipitation forecasting, and significant wave height forecasting. Fundamentals of both theoretical and practical aspects are discussed in varied domains....
Biographie: 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.
Sommaire: 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
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