1st Edition
Leveraging Artificial Intelligence in Engineering, Management, and Safety of Infrastructure
Chapter 1: Convolutional Neural Networks and Applications on Civil Infrastructure
Onur Avci, Osama Abdeljaber, Serkan Kiranyaz, Turker Ince, and Daniel J. Inman
Chapter 2: Identifying Non-linearity in Construction Workers' Personality: Safety Behaviour Predictive Relationship Using Neural Network and Linear Regression Modelling
Yifan Gao, Vicente A. González, Tak Wing Yiu, and Guillermo Cabrera-Guerrero
Chapter 3: Machine Learning Framework for Predicting Failure Mode and Flexural capacity of Frp-Reinforced Beams
Ahmad N. Tarawneh, and Eman F. Saleh
Chapter 4: A Novel Formulation for Estimating Compressive Strength of High Performance Concrete Using Gene Expression Programming
Iman Mansouri, Jale Tezcan, and Paul O. Awoyera
Chapter 5: Implementation of Data-Driven Approaches for Condition Assessment of Structures and Analyzing Complex Data
Vafa Soltangharaei, Li Ai, and Paul Ziehl
Chapter 6: Automatic Detection of Surface Thermal Cracks in Structural Concrete with Numerical Correlation Analysis
Diana Andrushia, Anand N, Richard Walls, Daniel Paul T, and Prince Arulraj
Chapter 7: State-of-the-Art Research in the Area of Artificial Intelligence with Specific Consideration to Civil Infrastructure, Construction Engineering and Management, and Safety
Islam H. El-adaway and Rayan H. Assaad
Chapter 8: Artificial Intelligence in Concrete Materials: A Scientometric View
Zhanzhao Li and Aleksandra Radlińska
Chapter 9: Active Learning Kriging-Based Reliability for Assessing the Safety of Structures: Theory and Application
Koosha Khorramian, and Fadi Oudah
Chapter 10: A Bayesian Estimation Technique for Multilevel Damage Classification in DBHM
William Lockea, Stefani Mokalledb, Omar Abuodehc, Laura Redmondd, and Christopher McMahane
Chapter 11: Machine Learning and IoT Data for Concrete Performance Testing and Analysis
Andrew Fahim, Tahmid Mehdi, Ali Taheri, Pouria Ghods, Aali Alizadeh and Sarah De Carufel
Chapter 12: Knowledge-enhanced Deep Learning for Efficient Response Estimation of Nonlinear Structures
Haifeng Wang and Teng Wu
Chapter 13: Damage Detection in Reinforced Concrete Girders by Finite Element and Artificial Intelligence Synergy
Hayder A. Rasheed, Ahmed Al-Rahmani, and AlaaEldin Abouelleil
Chapter 14: Deep Learning in Transportation Cyber-Physical Systems
Zadid Khan, Sakib Mahmud Khan, Mizanur Rahman, Mhafuzul Islam, and Mashrur Chowdhury
Chapter 15: Artificial Intelligence in the Construction Industry: Theory and Emerging Applications for the Future of Work
Amir H. Behzadan, Nipun D. Nath, and Reza Akhavian
Chapter 16: The Use of Machine Learning in Heat Transfer Analysis for Structural Fire Engineering Applications
Yavor Panev, Tom Parker and Panagiotis Kotsovinos
Chapter 17: Using Artificial Intelligence to Derive Temperature-Dependent Mechanical Properties of Ultra-High Performance Concrete
Srishti Banerji
Chapter 18: Smart Tunnel Fire Safety Management by Sensor Network and Artificial Intelligence
Xinyan Huang, Xiqiang Wu, Xiaoning Zhang and Asif Usmani
Biography
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.
