Machine Learning Applications in Civil Engineering (Woodhead Publishing Series in Civil and Structural Engineering) - Tapa blanda

Meshram

 
9780443153648: Machine Learning Applications in Civil Engineering (Woodhead Publishing Series in Civil and Structural Engineering)
Tapa blanda
ISBN 10: 0443153647 ISBN 13: 9780443153648
Editorial: Elsevier, 2023

Sinopsis

Machine Learning Applications in Civil Engineering discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods wherein internal processing is done using randomized prototypes. The book explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency. It introduces Machine Learning and its applications to different Civil Engineering tasks, including Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies. Using this book, civil engineering students and researchers can deep dive into Machine Learning, and identify various solutions to practical Civil Engineering tasks.

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Acerca del autor

Dr. Kundan Meshram is currently working as Assistant Professor, in the Department of Civil Engineering, at Guru Ghasidas Vishwavidyalaya (A Central University) Bilaspur (C.G.), India. He has received Ph.D. (Civil Engineering) from Maulana Azad National Institute of Technology Bhopal, India in 2016. His main research interest includes Pavement Material Characterization, Pavement Performance and Maintenance, Transportation Geotechnics, Road Safety, and Multimodal Transportation Systems. He has 05 patent and published 2 books, 3 book chapters and more 40 research papers in various International/National Journals, and Proceedings of reputed International/ National Conferences. He was awarded International Innovative Researcher in Civil Engineering, RULA Peace Award in 2019 and the CPWD Medal and Best Paper Award from the Indian Road Congress, for his paper ‘Pavement Deterioration Modeling for Low Volume Roads’ in 2015.

De la contraportada

Discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods, wherein internal processing is done using randomized prototypes, due to which indulgence of researchers for internal model design is not needed. Moreover, efficiency of these models is also very high when compared with linear models, due to which they must be deployed for various scenarios. Inspired by these observations, this book provides an insight to various Civil Engineering components, and discusses their design via deep learning models, which will assist readers to gain an edge against others in terms of practical design opportunities in Traffic Engineering, Transportation Engineering, Construction Materials, Geotechnical Engineering, Structural Engineering, Water Resources Engineering, Environmental Engineering, Remote sensing, GIS, Construction techniques and Management, thereby assisting them in exploration of suitable business avenues. As this book explains, various machine learning model designs, which will assist researchers to design multi domain systems with maximum efficiency, readers will also get a detailed review about different lacunas & challenges in current Civil Engineering based research components. These can be explored for designing customized components for an optimum system deployment. This book will initially cover introduction to Machine Learning, and its applications to different Civil Engineering tasks. This includes, Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies. Using this book, Civil Engineering students & researchers can deep dive into Machine Learning, and identify various solutions to practical Civil Engineering tasks.

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Editorial
Elsevier
Año de publicación
2023
Idioma
Inglés
ISBN 10 
0443153647
ISBN 13 
9780443153648
Encuadernación
Tapa blanda
Número de páginas
218
Contacto del fabricante
ELSEVIER
https://www.elsevier.com/es-es

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