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| emerging artificial intelligence methods in structural engineering: Artificial Intelligence in Structural Engineering Ian Smith, 1998-07-15 This book presents the state of the art of artificial intelligence techniques applied to structural engineering. The 28 revised full papers by leading scientists were solicited for presentation at a meeting held in Ascona, Switzerland, in July 1998. The recent advances in information technology, in particular decreasing hardware cost, Internet communication, faster computation, increased bandwidth, etc., allow for the application of new AI techniques to structural engineering. The papers presented deal with new aspects of information technology support for the design, analysis, monitoring, control and diagnosis of various structural engineering systems. |
| emerging artificial intelligence methods in structural engineering: Advances in Structural Engineering—Optimization Sinan Melih Nigdeli, Gebrail Bekdaş, Aylin Ece Kayabekir, Melda Yucel, 2020-12-04 This book is an up-to-date source for computation applications of optimization, prediction via artificial intelligence methods, and evaluation of metaheuristic algorithm with different structural applications. As the current interest of researcher, metaheuristic algorithms are a high interest topic area since advance and non-optimized problems via mathematical methods are challenged by the development of advance and modified algorithms. The artificial intelligence (AI) area is also important in predicting optimum results by skipping long iterative optimization processes. The machine learning used in generation of AI models also needs optimum results of metaheuristic-based approaches. This book is a great source to researcher, graduate students, and bachelor students who gain project about structural optimization. Differently from the academic use, the chapter that emphasizes different scopes and methods can take the interest and help engineer working in design and production of structural engineering projects. |
| emerging artificial intelligence methods in structural engineering: Artificial Intelligence and Machine Learning Techniques for Civil Engineering Plevris, Vagelis, Ahmad, Afaq, Lagaros, Nikos D., 2023-06-05 In recent years, artificial intelligence (AI) has drawn significant attention with respect to its applications in several scientific fields, varying from big data handling to medical diagnosis. A tremendous transformation has taken place with the emerging application of AI. AI can provide a wide range of solutions to address many challenges in civil engineering. Artificial Intelligence and Machine Learning Techniques for Civil Engineering highlights the latest technologies and applications of AI in structural engineering, transportation engineering, geotechnical engineering, and more. It features a collection of innovative research on the methods and implementation of AI and machine learning in multiple facets of civil engineering. Covering topics such as damage inspection, safety risk management, and information modeling, this premier reference source is an essential resource for engineers, government officials, business leaders and executives, construction managers, students and faculty of higher education, librarians, researchers, and academicians. |
| emerging artificial intelligence methods in structural engineering: Artificial Intelligence in Construction Engineering and Management Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski, 2021-06-18 This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally. |
| emerging artificial intelligence methods in structural engineering: Modeling and Simulation Techniques in Structural Engineering Samui, Pijush, Chakraborty, Subrata, Kim, Dookie, 2016-08-12 The development of new and effective analytical and numerical models is essential to understanding the performance of a variety of structures. As computational methods continue to advance, so too do their applications in structural performance modeling and analysis. Modeling and Simulation Techniques in Structural Engineering presents emerging research on computational techniques and applications within the field of structural engineering. This timely publication features practical applications as well as new research insights and is ideally designed for use by engineers, IT professionals, researchers, and graduate-level students. |
| emerging artificial intelligence methods in structural engineering: Applications of Artificial Intelligence in Process Systems Engineering Jingzheng Ren, Weifeng Shen, Yi Man, Lichun Dong, 2021-06-05 Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering |
| emerging artificial intelligence methods in structural engineering: Recent Developments in Structural Engineering, Volume 1 Manmohan Dass Goel, |
| emerging artificial intelligence methods in structural engineering: Proceedings of the 18th International Conference on Computing in Civil and Building Engineering Eduardo Toledo Santos, Sergio Scheer, 2020-07-14 This book gathers the latest advances, innovations, and applications in the field of information technology in civil and building engineering, presented at the 18th International Conference on Computing in Civil and Building Engineering (ICCCBE), São Paulo, Brazil, August 18-20, 2020. It covers highly diverse topics such as BIM, construction information modeling, knowledge management, GIS, GPS, laser scanning, sensors, monitoring, VR/AR, computer-aided construction, product and process modeling, big data and IoT, cooperative design, mobile computing, simulation, structural health monitoring, computer-aided structural control and analysis, ICT in geotechnical engineering, computational mechanics, asset management, maintenance, urban planning, facility management, and smart cities. Written by leading researchers and engineers, and selected by means of a rigorous international peer-review process, the contributions highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations. |
| emerging artificial intelligence methods in structural engineering: Handbook of AI-based Metaheuristics Anand J. Kulkarni, Patrick Siarry, 2021-09-01 At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains. |
| emerging artificial intelligence methods in structural engineering: Vibration-based Techniques For Damage Detection And Localization In Engineering Structures Ali Salehzadeh Nobari, M H Ferri Aliabadi, 2018-05-04 In the oil and gas industries, large companies are endeavoring to find and utilize efficient structural health monitoring methods in order to reduce maintenance costs and time. Through an examination of the vibration-based techniques, this title addresses theoretical, computational and experimental methods used within this trend.By providing comprehensive and up-to-date coverage of established and emerging processes, this book enables the reader to draw their own conclusions about the field of vibration-controlled damage detection in comparison with other available techniques. The chapters offer a balance between laboratory and practical applications, in addition to detailed case studies, strengths and weakness are drawn from a broad spectrum of information. |
| emerging artificial intelligence methods in structural engineering: Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures Raffaele Zinno, Serena Artese, 2021-09-02 In the past, when elements in structures were composed of perishable materials, such as wood, the maintenance of houses, bridges, etc., was considered of vital importance for their safe use and to preserve their efficiency. With the advent of materials such as reinforced concrete and steel, given their relatively long useful life, periodic and constant maintenance has often been considered a secondary concern. When it was realized that even for structures fabricated with these materials that the useful life has an end and that it was being approached, planning maintenance became an important and non-negligible aspect. Thus, the concept of structural health monitoring (SHM) was introduced, designed, and implemented as a multidisciplinary method. Computational mechanics, static and dynamic analysis of structures, electronics, sensors, and, recently, the Internet of Things (IoT) and artificial intelligence (AI) are required, but it is also important to consider new materials, especially those with intrinsic self-diagnosis characteristics, and to use measurement and survey methods typical of modern geomatics, such as satellite surveys and highly sophisticated laser tools. |
| emerging artificial intelligence methods in structural engineering: Intelligent Computational Paradigms in Earthquake Engineering Nikos D. Lagaros, Yiannis Tsompanakis, 2007-01-01 This book contains contributions that cover a wide spectrum of very important real-world engineering problems, and explores the implementation of neural networks for the representation of structural responses in earthquake engineering. It assesses the efficiency of seismic design procedures and describes the latest findings in intelligent optimal control systems and their applications in structural engineering--Provided by publisher. |
| emerging artificial intelligence methods in structural engineering: Artificial Intelligence and IoT Kalaiselvi Geetha Manoharan, Jawaharlal Arun Nehru, Sivaraman Balasubramanian, 2021-02-12 This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors’ intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors’ attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain. |
| emerging artificial intelligence methods in structural engineering: Artificial Intelligence Applications for Sustainable Construction Moncef L. Nehdi, Harish Chandra Arora, Krishna Kumar, Robertas Damaševičius, Aman Kumar, 2024-02-13 Artificial Intelligence Applications for Sustainable Construction presents the latest developments in AI and ML technologies applied to real-world civil engineering concerns. With an increasing amount of attention on the environmental impact of every industry, more construction projects are going to require sustainable construction practices. This volume offers research evidence, simulation results, and case studies to support this change. Sustainable construction, in fact, not only uses renewable and recyclable materials when building new structures or repairing deteriorating ones, but also adopts all possible methods to reduce energy consumption and waste. The concisely written but comprehensive, practical knowledge put forward by this international group of highly specialized editors and contributors will prove to be beneficial to engineering students and professionals alike. - Presents convincing success stories that encourage application of AI-powered tools to civil engineering - Provides a wealth of valuable technical information to address and resolve many challenging construction problems - Illustrates the most recent shifts in thinking and practice for sustainable construction |
| emerging artificial intelligence methods in structural engineering: Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering Gebrail Bekdas, Sinan Melih Nigdeli, Melda Yucel, 2019 This book examines the application of artificial intelligence and machine learning civil, mechanical, and industrial engineering-- |
| emerging artificial intelligence methods in structural engineering: Theoretical and Applied Mechanics Mario Di Paola, Livan Fratini, Fabrizio Micari, Antonina Pirrotta, 2023-04-25 The book presents the proceedings of the XXV National Congress of the Italian Association of Theoretical and Applied Mechanics (Palermo, September 2022). The topics cover theoretical, computational, experimental and technical-applicative aspects. Chapters: Fluid Mechanics, Solid Mechanics, Structural Mechanics, Mechanics of Machine, Computational Mechanics, Biomechanics, Masonry Modelling and Analysis, Dynamical Systems in Civil and Mechanical Structures, Control and Experimental Dynamics, Mechanical Modelling of Metamaterials and Periodic Structures, Novel Stochastic Dynamics, Signal Processing Techniques for Civil Engineering Applications, Vibration-based Monitoring and Dynamic Identification of Historic Constructions, Modeling and Analysis of Nanocomposites and Small-Scale Structures, Gradient Flows in Mechanics and Continuum Physics, Multibody Systems Vibration Analysis, Mechanics of Renewable Energy Systems, Mathematical Modeling and Experimental Techniques for Quantification and Prediction of Fluid Dynamic Noise, and Advanced Process Mechanics. Keywords: Fluid Mechanics, Solid Mechanics, Structural Mechanics, Mechanics of Machine, Computational Mechanics, Biomechanics, Masonry Modelling and Analysis, Dynamical Systems in Civil and Mechanical Structures, Control and Experimental Dynamics, Mechanical Modelling of Metamaterials and Periodic Structures, Novel Stochastic Dynamics, Signal Processing Techniques for Civil Engineering Applications, Vibration-based Monitoring and Dynamic Identification of Historic Constructions, Modeling and Analysis of Nanocomposites and Small-Scale Structures, Gradient Flows in Mechanics and Continuum Physics, Multibody Systems Vibration Analysis, Mechanics of Renewable Energy Systems, Mathematical Modeling and Experimental Techniques for Quantification and Prediction of Fluid Dynamic Noise, and Advanced Process Mechanics. |
| emerging artificial intelligence methods in structural engineering: Data Driven Methods for Civil Structural Health Monitoring and Resilience Mohammad Noori, Carlo Rainieri, Marco Domaneschi, Vasilis Sarhosis, 2023-10-26 Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers. |
| emerging artificial intelligence methods in structural engineering: Human Interaction & Emerging Technologies (IHIET 2022): Artificial Intelligence & Future Applications Tareq Ahram and Redha Taiar , 2022-07-24 Human Interaction & Emerging Technologies (IHIET 2022): Artificial Intelligence & Future Applications Proceedings of the 8th International Conference on Human Interaction & Emerging Technologies (IHIET 2022): Artificial Intelligence & Future Applications, August 22–24, 2022, Nice, France |
| emerging artificial intelligence methods in structural engineering: EG-ICE 2021 Workshop on Intelligent Computing in Engineering Abualdenien, Jimmy, Borrmann, André, Ungureanu, Lucian-Constantin, Hartmann, Timo, 2021-08-06 The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. Der 28. Internationale EG-ICE Workshop 2021 bringt internationale Experten zusammen, die an der Schnittstelle zwischen fortgeschrittener Datenverarbeitung und modernen technischen Herausforderungen arbeiten. Viele ingenieurwissenschaftliche Aufgaben erfordern Open-World-Resolutionen, um die Zusammenarbeit mehrerer Akteure zu unterstützen, mit approximativen Modellen umzugehen, eine effektive Interaktion zwischen Ingenieur und Computer zu ermöglichen, in mehrdimensionalen Lösungsräumen zu suchen, Unsicherheiten zu berücksichtigen, einschließlich fachspezifischen Domänenwissens, Sensordateninterpretation durchzuführen und mit unvollständigem Wissen umzugehen. Während die Ergebnisse aus der Informatik anfänglich viel Unterstützung für die Lösung bieten, ist eine Anpassung unvermeidlich, und am wichtigsten ist, dass das Feedback aus der Bewältigung technischer Herausforderungen die computer-wissenschaftliche Grundlagenforschung vorantreibt. Kompetenz und Wissenstransfer gehen in beide Richtungen. |
| emerging artificial intelligence methods in structural engineering: Modern Mechanics and Applications Nguyen Tien Khiem, Tran Van Lien, Nguyen Xuan Hung, 2021-09-06 This proceedings book includes a selection of refereed papers presented at the International Conference on Modern Mechanics and Applications (ICOMMA) 2020, which took place in Ho Chi Minh City, Vietnam, on December 2–4, 2020. The contributions highlight recent trends and applications in modern mechanics. Subjects covered include biological systems; damage, fracture, and failure; flow problems; multiscale multi-physics problems; composites and hybrid structures; optimization and inverse problems; lightweight structures; mechatronics; dynamics; numerical methods and intelligent computing; additive manufacturing; natural hazards modeling. The book is intended for academics, including graduate students and experienced researchers interested in recent trends in modern mechanics and application. |
| emerging artificial intelligence methods in structural engineering: Current Perspectives and New Directions in Mechanics, Modelling and Design of Structural Systems Alphose Zingoni, 2022-09-02 Current Perspectives and New Directions in Mechanics, Modelling and Design of Structural Systems comprises 330 papers that were presented at the Eighth International Conference on Structural Engineering, Mechanics and Computation (SEMC 2022, Cape Town, South Africa, 5-7 September 2022). The topics featured may be clustered into six broad categories that span the themes of mechanics, modelling and engineering design: (i) mechanics of materials (elasticity, plasticity, porous media, fracture, fatigue, damage, delamination, viscosity, creep, shrinkage, etc); (ii) mechanics of structures (dynamics, vibration, seismic response, soil-structure interaction, fluid-structure interaction, response to blast and impact, response to fire, structural stability, buckling, collapse behaviour); (iii) numerical modelling and experimental testing (numerical methods, simulation techniques, multi-scale modelling, computational modelling, laboratory testing, field testing, experimental measurements); (iv) design in traditional engineering materials (steel, concrete, steel-concrete composite, aluminium, masonry, timber); (v) innovative concepts, sustainable engineering and special structures (nanostructures, adaptive structures, smart structures, composite structures, glass structures, bio-inspired structures, shells, membranes, space structures, lightweight structures, etc); (vi) the engineering process and life-cycle considerations (conceptualisation, planning, analysis, design, optimization, construction, assembly, manufacture, maintenance, monitoring, assessment, repair, strengthening, retrofitting, decommissioning). Two versions of the papers are available: full papers of length 6 pages are included in the e-book, while short papers of length 2 pages, intended to be concise but self-contained summaries of the full papers, are in the printed book. This work will be of interest to civil, structural, mechanical, marine and aerospace engineers, as well as planners and architects. |
| emerging artificial intelligence methods in structural engineering: Computational Engineering Peter Debney, 2021 |
| emerging artificial intelligence methods in structural engineering: The Ethical Frontier of AI and Data Analysis Kumar, Rajeev, Joshi, Ankush, Sharan, Hari Om, Peng, Sheng-Lung, Dudhagara, Chetan R., 2024-03-04 In the advancing fields of artificial intelligence (AI) and data science, a pressing ethical dilemma arises. As technology continues its relentless march forward, ethical considerations within these domains become increasingly complex and critical. Bias in algorithms, lack of transparency, data privacy breaches, and the broader societal repercussions of AI applications are demanding urgent attention. This ethical quandary poses a formidable challenge for researchers, academics, and industry professionals alike, threatening the very foundation of responsible technological innovation. Navigating this ethical minefield requires a comprehensive understanding of the multifaceted issues at hand. The Ethical Frontier of AI and Data Analysis is an indispensable resource crafted to address the ethical challenges that define the future of AI and data science. Researchers and academics who find themselves at the forefront of this challenge are grappling with the evolving landscape of AI and data science ethics. Underscoring the need for this book is the current lack of clarity on ethical frameworks, bias mitigation strategies, and the broader societal implications, which hinder progress and leave a void in the discourse. As the demand for responsible AI solutions intensifies, the imperative for this reliable guide that consolidates, explores, and advances the dialogue on ethical considerations grows exponentially. |
| emerging artificial intelligence methods in structural engineering: Machine Learning for Engineers Ryan G. McClarren, 2021-09-21 All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging. This text teaches state-of-the-art machine learning technologies to students and practicing engineers from the traditionally “analog” disciplines—mechanical, aerospace, chemical, nuclear, and civil. Dr. McClarren examines these technologies from an engineering perspective and illustrates their specific value to engineers by presenting concrete examples based on physical systems. The book proceeds from basic learning models to deep neural networks, gradually increasing readers’ ability to apply modern machine learning techniques to their current work and to prepare them for future, as yet unknown, problems. Rather than taking a black box approach, the author teaches a broad range of techniques while conveying the kinds of problems best addressed by each. Examples and case studies in controls, dynamics, heat transfer, and other engineering applications are implemented in Python and the libraries scikit-learn and tensorflow, demonstrating how readers can apply the most up-to-date methods to their own problems. The book equally benefits undergraduate engineering students who wish to acquire the skills required by future employers, and practicing engineers who wish to expand and update their problem-solving toolkit. |
| emerging artificial intelligence methods in structural engineering: Research in Intelligent and Computing in Engineering Raghvendra Kumar, Nguyen Ho Quang, Vijender Kumar Solanki, Manuel Cardona, Prasant Kumar Pattnaik, 2021-01-04 This book comprises select peer-reviewed proceedings of the international conference on Research in Intelligent and Computing in Engineering (RICE 2020) held at Thu Dau Mot University, Vietnam. The volume primarily focuses on latest research and advances in various computing models such as centralized, distributed, cluster, grid, and cloud computing. Practical examples and real-life applications of wireless sensor networks, mobile ad hoc networks, and internet of things, data mining and machine learning are also covered in the book. The contents aim to enable researchers and professionals to tackle the rapidly growing needs of network applications and the various complexities associated with them. |
| emerging artificial intelligence methods in structural engineering: Structural Health Monitoring Charles R. Farrar, Keith Worden, 2012-11-19 Written by global leaders and pioneers in the field, this book is a must-have read for researchers, practicing engineers and university faculty working in SHM. Structural Health Monitoring: A Machine Learning Perspective is the first comprehensive book on the general problem of structural health monitoring. The authors, renowned experts in the field, consider structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm, first explaining the paradigm in general terms then explaining the process in detail with further insight provided via numerical and experimental studies of laboratory test specimens and in-situ structures. This paradigm provides a comprehensive framework for developing SHM solutions. Structural Health Monitoring: A Machine Learning Perspective makes extensive use of the authors’ detailed surveys of the technical literature, the experience they have gained from teaching numerous courses on this subject, and the results of performing numerous analytical and experimental structural health monitoring studies. Considers structural health monitoring in a new manner by casting the problem in the context of a machine learning/statistical pattern recognition paradigm Emphasises an integrated approach to the development of structural health monitoring solutions by coupling the measurement hardware portion of the problem directly with the data interrogation algorithms Benefits from extensive use of the authors’ detailed surveys of 800 papers in the technical literature and the experience they have gained from teaching numerous short courses on this subject. |
| emerging artificial intelligence methods in structural engineering: Data-Driven Science and Engineering Steven L. Brunton, J. Nathan Kutz, 2022-05-05 A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®. |
| emerging artificial intelligence methods in structural engineering: Structural Health Monitoring Using Emerging Signal Processing Approaches with Artificial Intelligence Algorithms Chunwei Zhang, Asma A. Mousavi, 2024-11-06 Structural health monitoring is a powerful tool across civil, mechanical, automotive, and aerospace engineering, allowing the assessment and measurement of physical parameters in real time. Processing changes in the vibration signals of a dynamic system can detect, locate, and quantify any damage existing in the system. This book presents a comprehensive state‐of‐the‐art review of the applications in time, frequency, and time‐frequency domains of signal‐processing techniques for damage perception, localization, and quantification in various structural systems. Experimental investigations are illustrated, including the development of a set of damage indices based on the signal features extracted through various signal‐processing techniques to evaluate sensitivity in damage identification. Chapters summarize the application of the Hilbert–Huang transform based on three decomposition methods such as empirical mode decomposition, ensemble empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise. Also, the chapters assess the performance and sensitivity of different approaches, including multiple signal classification and empirical wavelet transform techniques in damage detection and quantification. Artificial neural networks for automated damage identification are introduced. This book suits students, engineers, and researchers who are investigating structural health monitoring, signal processing, and damage identification of structures. |
| emerging artificial intelligence methods in structural engineering: Recent Advances in Civil Engineering Krishna R. Reddy, |
| emerging artificial intelligence methods in structural engineering: Applications of Machine Learning Prashant Johri, Jitendra Kumar Verma, Sudip Paul, 2020-05-04 This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics. |
| emerging artificial intelligence methods in structural engineering: Advances in Interdisciplinary Engineering Niraj Kumar, Szalay Tibor, Rahul Sindhwani, Jaesun Lee, Priyank Srivastava, 2021-04-12 This book comprises the select proceedings of the International Conference on Future Learning Aspects of Mechanical Engineering (FLAME) 2020. This volume focuses on several emerging interdisciplinary areas involving mechanical engineering. Some of the topics covered include automobile engineering, mechatronics, applied mechanics, structural mechanics, hydraulic mechanics, human vibration, biomechanics, biomedical Instrumentation, ergonomics, biodynamic modeling, nuclear engineering, and agriculture engineering. The contents of this book will be useful for students, researchers as well as professionals interested in interdisciplinary topics of mechanical engineering. |
| emerging artificial intelligence methods in structural engineering: Interpretable Machine Learning Christoph Molnar, 2020 This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project. |
| emerging artificial intelligence methods in structural engineering: Advanced AI and Internet of Health Things for Combating Pandemics Mohamed Lahby, Virginia Pilloni, Jyoti Sekhar Banerjee, Mufti Mahmud, 2023-07-24 This book presents the latest research, theoretical methods, and novel applications in the field of Health 5.0. The authors focus on combating COVID-19 or other pandemics through facilitating various technological services. The authors discuss new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 or other pandemic based on machine intelligence models and communication technologies. The aim of the coverage is to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence and Internet of Medical Things (IoMT). This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics. |
| emerging artificial intelligence methods in structural engineering: The Economics of Artificial Intelligence Ajay Agrawal, Joshua Gans, Avi Goldfarb, Catherine Tucker, 2024-03-05 A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system. |
| emerging artificial intelligence methods in structural engineering: Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0 D. Jude Hemanth, |
| emerging artificial intelligence methods in structural engineering: Advances in Structural Engineering-Optimization Sinan Melih Nigdeli, Gebrail Bekdaş, Aylin Ece Kayabekir, Melda Yucel, 2021 This book is an up-to-date source for computation applications of optimization, prediction via artificial intelligence methods, and evaluation of metaheuristic algorithm with different structural applications. As the current interest of researcher, metaheuristic algorithms are a high interest topic area since advance and non-optimized problems via mathematical methods are challenged by the development of advance and modified algorithms. The artificial intelligence (AI) area is also important in predicting optimum results by skipping long iterative optimization processes. The machine learning used in generation of AI models also needs optimum results of metaheuristic-based approaches. This book is a great source to researcher, graduate students, and bachelor students who gain project about structural optimization. Differently from the academic use, the chapter that emphasizes different scopes and methods can take the interest and help engineer working in design and production of structural engineering projects. |
| emerging artificial intelligence methods in structural engineering: Advances in Construction Materials and Management Aneetha Vilventhan, |
| emerging artificial intelligence methods in structural engineering: ECPPM 2021 - eWork and eBusiness in Architecture, Engineering and Construction Vitaly Semenov, Raimar J Scherer, 2021-04-28 eWork and eBusiness in Architecture, Engineering and Construction 2021 collects the papers presented at the 13th European Conference on Product and Process Modelling (ECPPM 2021, Moscow, 5-7 May 2021). The contributions cover a wide spectrum of thematic areas that hold great promise towards the advancement of research and technological development targeted at the digitalization of the AEC/FM (Architecture, Engineering, Construction and Facilities Management) domains. High quality contributions are devoted to critically important problems that arise, including: Information and Knowledge Management Semantic Web and Linked Data Communication and Collaboration Technologies Software Interoperability BIM Servers and Product Lifecycle Management Systems Digital Twins and Cyber-Physical Systems Sensors and Internet of Things Big Data Artificial and Augmented Intelligence in AEC Construction Management 5D/nD Modelling and Planning Building Performance Simulation Contract, Cost and Risk Management Safety and Quality Sustainable Buildings and Urban Environments Smart Buildings and Cities BIM Standardization, Implementation and Adoption Regulatory and Legal Aspects BIM Education and Training Industrialized Production, Smart Products and Services Over the past quarter century, the biennial ECPPM conference series, as the oldest BIM conference, has provided researchers and practitioners with a unique platform to present and discuss the latest developments regarding emerging BIM technologies and complementary issues for their adoption in the AEC/FM industry. |
| emerging artificial intelligence methods in structural engineering: Optimization for Decision Making II Víctor Yepes, José M. Moreno-Jiménez, 2020-11-25 In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner. |
| emerging artificial intelligence methods in structural engineering: Advanced Optimization Applications in Engineering Ahmad, Afaq, Camp, Charles V., 2024-05-20 In the ever-evolving landscape of engineering, a pressing challenge looms largethe need to navigate the complexities of modern problems with precision and efficiency. As industries grapple with an array of intricate issues, from sustainable materials to resilient infrastructure, the demand for optimal solutions has never been more pronounced. Traditional approaches are often inadequate, prompting the search for advanced optimization techniques capable of unraveling the intricacies inherent in engineering systems. The problem at hand is clear: how can engineers, researchers, and practitioners harness cutting-edge methodologies to address the multifaceted challenges shaping our technological future? Advanced Optimization Applications in Engineering, is a definitive guide poised to revolutionize problem-solving in civil engineering. This book offers a comprehensive exploration of state-of-the-art optimization algorithms and their transformative applications. By delving into genetic algorithms, particle swarm optimization, neural networks, and other metaheuristic strategies, this collection provides a roadmap for automating design processes, reducing costs, and unlocking innovative solutions. The chapters not only introduce these advanced techniques but also showcase their practical implementation across diverse engineering domains, making this book an indispensable resource for those seeking to stay at the forefront of technological advancements. |
Emerging artificial intelligence methods in structural …
Among the different AI techniques, machine learning (ML), pattern recognition (PR), and deep learning (DL) have acquired considerable attention and are establishing themselves as a new …
Artificial Intelligence, Machine Learning, and Deep Learning in ...
Artificial Intelligence, Machine Learning, and Deep Learning in Structural Engineering: A Scientometrics Review of Trends and Best Practices. Archives of Computational Methods in …
How Artificial Intelligence (AI) is Being Utilized in Structural ...
The purpose of this research is to explore how AI is being utilized in structural engineering. This includes examining the specific AI techniques employed, the applications of AI in different …
DELVE IN THE NEW ERA: ARTIFICIAL INTELLIGENCE IN …
Artificial Intelligence proves to be the most promising path to more efficient practices in civil engineering. AI can be successfully implemented as a vital game changer in the field of …
Emerging artificial intelligence methods in structural …
Among the di erent AI techniques, machine ffi ff learning (ML), pattern recognition (PR), and deep learning (DL) have recently acquired considerable attention and are establishing themselves …
Artificial Intelligence Integration in Structural Design and …
Feb 20, 2024 · Artificial Neural Networks (ANN) have gained prominence in different aspects of construction. The integration of PR and ML in structural engineering has been particularly …
Emerging Applications of Artificial Intelligence in Structural ...
Emerging AI Branches in Structural Engineering and Construction Industry. Considering the various disciplines of AI such as Deep Learning, Pattern Recognition, Machine Learning, …
Artificial Intelligence Construction Engineering Management
to make machines mimic human cognitive processes in terms of learning, reasoning, and self-correcting. Relying on the important AI approaches, we put emphasis on nine hot research …
5 WAYS TECHNOLOGY IS SHIFTING THE STRUCTURAL …
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are relatively new techniques capable of providing the engineering community with affordable
Artificial Intelligence, Machine Learning, and Deep Learning in ...
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging techniques capable of delivering elegant and afordable solutions which can surpass those obtained …
International Journal of Innovative Research in Science
ABSTRACT: AI in structural engineering holds immense promise for the industry. With its ability to automate analysis and design processes, improve accuracy, and enable real-time monitoring, …
Modern Structural Engineering Techniques Utilizing Artificial …
AI has the potential to revolutionize the field of structural engineering. By enabling engineers to design more efficient structures, simulate their behavior more accurately, detect damage and …
ISO 3297:2007 Certified Application of Artificial Using …
Salehi, et.al[34] (2018) “Emerging artificial intelligence methods in structural engineering” this study focuses on Artificial intelligence (AI) has emerged as a powerful alternative to traditional …
EMERGING ARTIFICIAL INTELLIGENCE METHODS IN …
intelligence methods that are increasingly emerging as reliable and efficient tools in the field of structural engineering. This section provides technical background on the noted methods
Emerging artificial intelligence methods in structural …
The objective of this review paper is to summarize recently developed techniques with regards to the applications of the noted AI methods in structural engineering over the last decade....
A REVIEW PAPER ON THE USE OF ARTIFICIAL INTELLIGENT …
The importance of AI in structural engineering along with the application of Machine Learning (ML), Pattern Recognition (PR), and Deep Learning (DL) was discussed.
APPLICATION OF EMERGING ARTIFICIAL INTELLIGENCE …
Among the different AI techniques, machine learning (ML), pattern recognition (PR), and deep learning (DL) have recently acquired considerable attention and are establishing themselves …
Emerging artificial intelligence methods in structural …
objective of this review paper is to summarize techniques concerning applications of the noted AI methods in structural engineering developed over the last decade. First, a general introduction …
Emerging Artificial Intelligence Methods In Structural …
Intelligence in Structural Engineering Ian Smith,1998 This book presents the state of the art of artificial intelligence techniques applied to structural engineering The 28 revised full papers by …
Emerging artificial intelligence methods in structural …
Among the different AI techniques, machine learning (ML), pattern recognition (PR), and deep learning (DL) have acquired considerable attention and are establishing themselves as a new …
Artificial Intelligence, Machine Learning, and Deep Learning …
Artificial Intelligence, Machine Learning, and Deep Learning in Structural Engineering: A Scientometrics Review of Trends and Best Practices. Archives of Computational Methods in …
How Artificial Intelligence (AI) is Being Utilized in Structural ...
The purpose of this research is to explore how AI is being utilized in structural engineering. This includes examining the specific AI techniques employed, the applications of AI in different …
DELVE IN THE NEW ERA: ARTIFICIAL INTELLIGENCE IN …
Artificial Intelligence proves to be the most promising path to more efficient practices in civil engineering. AI can be successfully implemented as a vital game changer in the field of …
Emerging artificial intelligence methods in structural …
Among the di erent AI techniques, machine ffi ff learning (ML), pattern recognition (PR), and deep learning (DL) have recently acquired considerable attention and are establishing themselves …
Artificial Intelligence Integration in Structural Design and …
Feb 20, 2024 · Artificial Neural Networks (ANN) have gained prominence in different aspects of construction. The integration of PR and ML in structural engineering has been particularly …
Emerging Applications of Artificial Intelligence in Structural ...
Emerging AI Branches in Structural Engineering and Construction Industry. Considering the various disciplines of AI such as Deep Learning, Pattern Recognition, Machine Learning, …
Artificial Intelligence Construction Engineering Management
to make machines mimic human cognitive processes in terms of learning, reasoning, and self-correcting. Relying on the important AI approaches, we put emphasis on nine hot research …
5 WAYS TECHNOLOGY IS SHIFTING THE STRUCTURAL …
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are relatively new techniques capable of providing the engineering community with affordable
Artificial Intelligence, Machine Learning, and Deep Learning …
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging techniques capable of delivering elegant and afordable solutions which can surpass those obtained …
International Journal of Innovative Research in Science
ABSTRACT: AI in structural engineering holds immense promise for the industry. With its ability to automate analysis and design processes, improve accuracy, and enable real-time monitoring, …
Modern Structural Engineering Techniques Utilizing …
AI has the potential to revolutionize the field of structural engineering. By enabling engineers to design more efficient structures, simulate their behavior more accurately, detect damage and …
ISO 3297:2007 Certified Application of Artificial Using …
Salehi, et.al[34] (2018) “Emerging artificial intelligence methods in structural engineering” this study focuses on Artificial intelligence (AI) has emerged as a powerful alternative to traditional …
EMERGING ARTIFICIAL INTELLIGENCE METHODS IN …
intelligence methods that are increasingly emerging as reliable and efficient tools in the field of structural engineering. This section provides technical background on the noted methods
Emerging artificial intelligence methods in structural …
The objective of this review paper is to summarize recently developed techniques with regards to the applications of the noted AI methods in structural engineering over the last decade....
A REVIEW PAPER ON THE USE OF ARTIFICIAL INTELLIGENT …
The importance of AI in structural engineering along with the application of Machine Learning (ML), Pattern Recognition (PR), and Deep Learning (DL) was discussed.
APPLICATION OF EMERGING ARTIFICIAL INTELLIGENCE …
Among the different AI techniques, machine learning (ML), pattern recognition (PR), and deep learning (DL) have recently acquired considerable attention and are establishing themselves …
Emerging artificial intelligence methods in structural …
objective of this review paper is to summarize techniques concerning applications of the noted AI methods in structural engineering developed over the last decade. First, a general introduction …
Emerging Artificial Intelligence Methods In Structural …
Intelligence in Structural Engineering Ian Smith,1998 This book presents the state of the art of artificial intelligence techniques applied to structural engineering The 28 revised full papers by …
