Machine Learning for Civil and Environmental Engineers : (Record no. 6592)

MARC details
000 -LEADER
fixed length control field 02922 a2200193 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251014145459.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 241202b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119897606
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Item number NasM
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Naser, M. Z.
245 ## - TITLE STATEMENT
Title Machine Learning for Civil and Environmental Engineers :
Remainder of title A Practical Approach to Data-Driven Analysis, Explainability, and Causality /
Statement of responsibility, etc M. Z. Naser
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication New Jersey :
Name of publisher Wiley,
Year of publication ©2023.
300 ## - PHYSICAL DESCRIPTION
Number of Pages xix, 588p.
520 ## - SUMMARY, ETC.
Summary, etc Accessible and practical framework for machine learning applications and solutions for civil and environmental engineers<br/><br/>This textbook introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain.<br/><br/>Through real-world projects like analysis and design of structural members, optimizing concrete mixtures for site applications, examining concrete cracking via computer vision, evaluating the response of bridges to hazards, and predicating water quality and energy expenditure in buildings, this textbook offers readers in-depth case studies with solved problems that are commonly faced by civil and environmental engineers.<br/><br/>The approaches presented range from simplified to advanced methods, incorporating coding-based and coding-free techniques. Professional engineers and engineering students will find value in the step-by-step examples that are accompanied by sample databases and codes for readers to practice with.<br/><br/>Written by a highly qualified professional with significant experience in the field, Machine Learning includes valuable information on:<br/><br/>The current state of machine learning and causality in civil and environmental engineering as viewed through a scientometrics analysis, plus a historical perspective<br/>Supervised vs. unsupervised learning for regression, classification, and clustering problems<br/>Explainable and causal methods for practical engineering problems<br/>Database development, outlining how an engineer can effectively collect and verify appropriate data to be used in machine intelligence analysis<br/>A framework for machine learning adoption and application, covering key questions commonly faced by practitioners<br/>This textbook is a must-have reference for undergraduate/graduate students to learn concepts on the use of machine learning, for scientists/researchers to learn how to integrate machine learning into civil and environmental engineering, and for design/engineering professionals as a reference guide for undertaking MI design, simulation, and optimization for infrastructure.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Civil engineering
General subdivision Data processing
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Collection code Home library Current library Shelving location Date acquired Source of acquisition Purchase Price Bill number Full call number Accession Number Copy number Print Price Bill Date/Price effective from Koha item type
      Civil Engineering Indian Institute of Technology Tirupati Indian Institute of Technology Tirupati General Stacks 14/10/2025 Creative Books 4910.64 CB/25128 006.31 NasM (11685) 11685 Copy 01 7015.20 14/10/2025 Books