Data Science For Civil Engineering
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Data Science For Civil Engineering
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Author : Rakesh K. Jain
language : en
Publisher: CRC Press
Release Date : 2023-05-10
Data Science For Civil Engineering written by Rakesh K. Jain and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-10 with Computers categories.
This book explains use of data science-based techniques for modeling and providing optimal solutions to complex problems in civil engineering. It discusses civil engineering problems like air, water and land pollution, climate crisis, transportation infrastructures, traffic and travel modes, mobility services, and so forth. Divided into two sections, the first one deals with the basics of data science and essential mathematics while the second section covers pertinent applications in structural and environmental engineering, construction management, and transportation. Features: Details information on essential mathematics required to implement civil engineering applications using data science techniques. Discusses broad background of data science and its fundamentals. Focusses on structural engineering, transportation systems, water resource management, geomatics, and environmental engineering. Includes python programming libraries to solve complex problems. Addresses various real-world applications of data science based civil engineering use cases. This book aims at senior undergraduate students in Civil Engineering and Applied Data Science.
Foundations Of Data Science For Engineering Problem Solving
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Author : Parikshit Narendra Mahalle
language : en
Publisher:
Release Date : 2022
Foundations Of Data Science For Engineering Problem Solving written by Parikshit Narendra Mahalle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.
Structural Health Monitoring Based On Data Science Techniques
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Author : Alexandre Cury
language : en
Publisher: Springer Nature
Release Date : 2021-10-23
Structural Health Monitoring Based On Data Science Techniques written by Alexandre Cury and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-23 with Computers categories.
The modern structural health monitoring (SHM) paradigm of transforming in situ, real-time data acquisition into actionable decisions regarding structural performance, health state, maintenance, or life cycle assessment has been accelerated by the rapid growth of “big data” availability and advanced data science. Such data availability coupled with a wide variety of machine learning and data analytics techniques have led to rapid advancement of how SHM is executed, enabling increased transformation from research to practice. This book intends to present a representative collection of such data science advancements used for SHM applications, providing an important contribution for civil engineers, researchers, and practitioners around the world.
A Primer On Machine Learning Applications In Civil Engineering
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Author : Paresh Chandra Deka
language : en
Publisher: CRC Press
Release Date : 2019-10-28
A Primer On Machine Learning Applications In Civil Engineering written by Paresh Chandra Deka and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-28 with Computers categories.
Machine learning has undergone rapid growth in diversification and practicality, and the repertoire of techniques has evolved and expanded. The aim of this book is to provide a broad overview of the available machine-learning techniques that can be utilized for solving civil engineering problems. The fundamentals of both theoretical and practical aspects are discussed in the domains of water resources/hydrological modeling, geotechnical engineering, construction engineering and management, and coastal/marine engineering. Complex civil engineering problems such as drought forecasting, river flow forecasting, modeling evaporation, estimation of dew point temperature, modeling compressive strength of concrete, ground water level forecasting, and significant wave height forecasting are also included. Features Exclusive information on machine learning and data analytics applications with respect to civil engineering Includes many machine learning techniques in numerous civil engineering disciplines Provides ideas on how and where to apply machine learning techniques for problem solving Covers water resources and hydrological modeling, geotechnical engineering, construction engineering and management, coastal and marine engineering, and geographical information systems Includes MATLAB® exercises
Probabilistic Machine Learning For Civil Engineers
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Author : James-A. Goulet
language : en
Publisher: MIT Press
Release Date : 2020-03-16
Probabilistic Machine Learning For Civil Engineers written by James-A. Goulet and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-16 with Computers categories.
An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises. This book introduces probabilistic machine learning concepts to civil engineering students and professionals, presenting key approaches and techniques in a way that is accessible to readers without a specialized background in statistics or computer science. It presents different methods clearly and directly, through step-by-step examples, illustrations, and exercises. Having mastered the material, readers will be able to understand the more advanced machine learning literature from which this book draws. The book presents key approaches in the three subfields of probabilistic machine learning: supervised learning, unsupervised learning, and reinforcement learning. It first covers the background knowledge required to understand machine learning, including linear algebra and probability theory. It goes on to present Bayesian estimation, which is behind the formulation of both supervised and unsupervised learning methods, and Markov chain Monte Carlo methods, which enable Bayesian estimation in certain complex cases. The book then covers approaches associated with supervised learning, including regression methods and classification methods, and notions associated with unsupervised learning, including clustering, dimensionality reduction, Bayesian networks, state-space models, and model calibration. Finally, the book introduces fundamental concepts of rational decisions in uncertain contexts and rational decision-making in uncertain and sequential contexts. Building on this, the book describes the basics of reinforcement learning, whereby a virtual agent learns how to make optimal decisions through trial and error while interacting with its environment.
Civil And Environmental Engineering Concepts Methodologies Tools And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2016-01-31
Civil And Environmental Engineering Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-31 with Technology & Engineering categories.
Civil and environmental engineers work together to develop, build, and maintain the man-made and natural environments that make up the infrastructures and ecosystems in which we live and thrive. Civil and Environmental Engineering: Concepts, Methodologies, Tools, and Applications is a comprehensive multi-volume publication showcasing the best research on topics pertaining to road design, building maintenance and construction, transportation, earthquake engineering, waste and pollution management, and water resources management and engineering. Through its broad and extensive coverage on a variety of crucial concepts in the field of civil engineering, and its subfield of environmental engineering, this multi-volume work is an essential addition to the library collections of academic and government institutions and appropriately meets the research needs of engineers, environmental specialists, researchers, and graduate-level students.
Mechanistic Data Science For Stem Education And Applications
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Author : Wing Kam Liu
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
Mechanistic Data Science For Stem Education And Applications written by Wing Kam Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.
This book introduces Mechanistic Data Science (MDS) as a structured methodology for combining data science tools with mathematical scientific principles (i.e., “mechanistic” principles) to solve intractable problems. Traditional data science methodologies require copious quantities of data to show a reliable pattern, but the amount of required data can be greatly reduced by considering the mathematical science principles. MDS is presented here in six easy-to-follow modules: 1) Multimodal data generation and collection, 2) extraction of mechanistic features, 3) knowledge-driven dimension reduction, 4) reduced order surrogate models, 5) deep learning for regression and classification, and 6) system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for solving engineering problems as well as real-life problems. This book is written in a spectral style and is ideal as an entry level textbook for engineering and data science undergraduate and graduate students, practicing scientists and engineers, as well as STEM (Science, Technology, Engineering, Mathematics) high school students and teachers.
Intelligent Data Analytics For Decision Support Systems In Hazard Mitigation
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Author : Ravinesh C. Deo
language : en
Publisher: Springer Nature
Release Date : 2020-07-29
Intelligent Data Analytics For Decision Support Systems In Hazard Mitigation written by Ravinesh C. Deo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-29 with Technology & Engineering categories.
This book highlights cutting-edge applications of machine learning techniques for disaster management by monitoring, analyzing, and forecasting hydro-meteorological variables. Predictive modelling is a consolidated discipline used to forewarn the possibility of natural hazards. In this book, experts from numerical weather forecast, meteorology, hydrology, engineering, agriculture, economics, and disaster policy-making contribute towards an interdisciplinary framework to construct potent models for hazard risk mitigation. The book will help advance the state of knowledge of artificial intelligence in decision systems to aid disaster management and policy-making. This book can be a useful reference for graduate student, academics, practicing scientists and professionals of disaster management, artificial intelligence, and environmental sciences.
Proceedings Of Workshop On Interdisciplinary Sciences 2023
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Author : Ton Viet Ta
language : en
Publisher: Springer Nature
Release Date : 2024-10-20
Proceedings Of Workshop On Interdisciplinary Sciences 2023 written by Ton Viet Ta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-20 with Mathematics categories.
This volume features a selection of technical papers presented at the workshop “The Fifth Workshop on Interdisciplinary Sciences (WIS 2023)". Contributions from esteemed researchers and academics in applied mathematics, AI, and statistics offer valuable insights into their latest research. The papers also delve into interdisciplinary applications, spanning fields such as agriculture and economics, with strong emphasis on data analysis techniques. We hope this proceedings volume will serve as a valuable resource for scholars, researchers, and practitioners interested in the recent advancements and emerging trends in interdisciplinary sciences.
A Hands On Introduction To Data Science
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Author : Chirag Shah
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-02
A Hands On Introduction To Data Science written by Chirag Shah and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Business & Economics categories.
An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.