Deka, Paresh Chandra.
A Primer on Machine Learning Applications in Civil Engineering [electronic resource]. - Milton : CRC Press LLC, 2019. - 1 online resource (281 pages)
Description based upon print version of record.
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
9780429836664 042983666X 9780429451423 0429451423 9780429836657 0429836651 9780429836640 0429836643
Civil engineering.
Machine learning.
COMPUTERS / Machine Theory
MATHEMATICS / Arithmetic
TECHNOLOGY / Engineering / Civil
TA153
624
A Primer on Machine Learning Applications in Civil Engineering [electronic resource]. - Milton : CRC Press LLC, 2019. - 1 online resource (281 pages)
Description based upon print version of record.
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
9780429836664 042983666X 9780429451423 0429451423 9780429836657 0429836651 9780429836640 0429836643
Civil engineering.
Machine learning.
COMPUTERS / Machine Theory
MATHEMATICS / Arithmetic
TECHNOLOGY / Engineering / Civil
TA153
624