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Leveraging Artificial Intelligence in Engineering, Management, and Safety of Infrastructure [Kõva köide]

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  • Formaat: Hardback, 446 pages, kõrgus x laius: 234x156 mm, kaal: 1010 g, 63 Tables, black and white; 2 Line drawings, color; 150 Line drawings, black and white; 6 Halftones, color; 36 Halftones, black and white; 8 Illustrations, color; 186 Illustrations, black and white
  • Ilmumisaeg: 17-Nov-2022
  • Kirjastus: CRC Press
  • ISBN-10: 0367422107
  • ISBN-13: 9780367422103
  • Formaat: Hardback, 446 pages, kõrgus x laius: 234x156 mm, kaal: 1010 g, 63 Tables, black and white; 2 Line drawings, color; 150 Line drawings, black and white; 6 Halftones, color; 36 Halftones, black and white; 8 Illustrations, color; 186 Illustrations, black and white
  • Ilmumisaeg: 17-Nov-2022
  • Kirjastus: CRC Press
  • ISBN-10: 0367422107
  • ISBN-13: 9780367422103
"The design, construction, and upkeep of infrastructure comprises of a multitude of dimensions spanning a highly complex paradigm of interconnecting opportunities and challenges. While traditional methods fall short of adequately accounting for such complexity, fortunately, artificial intelligence (AI) presents novel and out-of-the-box solutions that can effectively tackle growing demands of modern and aging infrastructure including specifics regarding to structural design, traffic planning, energy requirements, human behavior etc. - especially in this era where infrastructure is reaching new heights, serving larger populations, and expected to withstand increasing natural and manmade threats. All in, this book highlights the growing inertia of utilizingAI to realize contemporary, smart and safe infrastructure. This is an emerging area that has not fully matured and is expected to draw considerable interest, attention and research in the years to come. This book marks a tangible attempt into assembling relative works, of interdisciplinary backgrounds, to a state-of-the-art handbook. In a sense, this book presents results of innovative efforts supplemented with case studies that can be used as benchmarks to carryout future experiments and/or facilitate development of advanced numerical models. Thus, this handbook aims to revolutionize the state of infrastructural engineering and sciences through fostering a new set of approaches that capitalizes on AI as their main drive. This book is written with the intention to serve as a guide for a wide audience including graduate and senior undergraduate students, professionals and government officials of civil, traffic and computer engineering backgrounds as well as for those engaged in urban planning discipline and human sciences"--

This unique book showcases the applications of various sub-fields of artificial intelligence (AI) in engineering, management and safety aspects of infrastructure.

Dedication iii
Preface iv
1 Convolutional Neural Networks and Applications on Civil Infrastructure
1(29)
Onur Avci
Osama Abdeljaber
Serkan Kiranyaz
Turker Ince
Daniel J. Inman
2 Identifying Non-linearity in Construction Workers' Personality: Safety Behaviour Predictive Relationship Using Neural Network and Linear Regression Modelling
30(22)
Yifan Gao
Vicente A. Gonzalez
Tak Wing Yiu
Guillermo Cabrera-Guerrero
3 Machine Learning Framework for Predicting Failure Mode and Flexural Capacity of FRP-Reinforced Beams
52(22)
Ahmad N. Tarawneh
Eman F. Saleh
4 A Novel Formulation for Estimating Compressive Strength of High Performance Concrete Using Gene Expression Programming
74(17)
Iman Mansouri
Jale Tezcan
Paul O. Awoyera
5 Implementation of Data-Driven Approaches for Condition Assessment of Structures and Analyzing Complex Data
91(29)
Vafa Soltangharaei
Li Ai
Paul Ziehl
6 Automatic Detection of Surface Thermal Cracks in Structural Concrete with Numerical Correlation Analysis
120(20)
Diana Andrushia
N. Anand
Richard Walls
T. Daniel Paul
Prince Arulraj
7 State-of-the-Art Research in the Area of Artificial Intelligence with Specific Consideration to Civil Infrastructure, Construction Engineering and Management, and Safety
140(21)
Islam H. El-adaway
Rayan H. Assaad
8 Artificial Intelligence in Concrete Materials: A Scientometric View
161(23)
Zhanzhao Li
Aleksandra Radlinska
9 Active Learning Kriging-Based Reliability for Assessing the Safety of Structures: Theory and Application
184(48)
Koosha Khorramian
Fadi Oudah
10 A Bayesian Estimation Technique for Multilevel Damage Classification in DBHM
232(29)
William Locke
Stefani Mokalled
Omar Abuodeh
Laura Redmond
Christopher McMahan
11 Machine Learning and IoT Data for Concrete Performance Testing and Analysis
261(14)
Andrew Fahim
Tahmid Mehdi
Ali Taheri
Pouria Ghods
Aali Alizadeh
Sarah De Carufel
12 Knowledge-enhanced Deep Learning for Efficient Response Estimation of Nonlinear Structures
275(23)
Haifeng Wang
Teng Wu
13 Damage Detection in Reinforced Concrete Girders by Finite Element and Artificial Intelligence Synergy
298(33)
Hayder A. Rasheed
Ahmed Al-Rahmani
AlaaEldin Abouelleil
14 Deep Learning in Transportation Cyber-Physical Systems
331(17)
Zadid Khan
Sakib Mahmud Khan
Mizanur Rahman
Mhafuzul Islam
Mashrur Chowdhury
15 Artificial Intelligence in the Construction Industry: Theory and Emerging Applications for the Future of Work
348(32)
Amir H. Behzadan
Nipun D. Nath
Reza Akhavian
16 The Use of Machine Learning in Heat Transfer Analysis for Structural Fire Engineering Applications
380(23)
Yavor Panev
Tom Parker
Panagiotis Kotsovinos
17 Using Artificial Intelligence to Derive Temperature Dependent Mechanical Properties of Ultra-High Performance Concrete
403(20)
Srishti Banerji
18 Smart Tunnel Fire Safety Management by Sensor Network and Artificial Intelligence
423(22)
Xinyan Huang
Xiqiang Wu
Xiaoning Zhang
Asif Usmani
Index 445
M.Z. Naser is a tenure-track faculty member at the School of Civil and Environmental Engineering & Earth Sciences, a member of the AI Research Institute for Science and Engineering (AIRISE) at Clemson University, USA. Dr. Naser has co-authored over 100 publications and has 10 years of experience in structural engineering and AI. His research interest spans causal & explainable AI methodologies to discover new knowledge hidden within the domains of structural & fire engineering and materials science to realize functional, sustainable, and resilient infrastructure. He is a registered professional engineer and a member of various international editorial boards and building committees.