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About the Authors
Preface
Chapter 1 Introduction
1.1 Introduction
1.2 Data Science: An Overview
1.3 Benefits, Challenges, and Applications of Data Science
1.4 Data Science and Civil Engineering: Opportunities
1.5 Summary of the Book
References
Chapter 2 Mathematical Foundation for Data Science
2.1 Linear Algebra
2.2 Calculus and Optimization Techniques
2.3 Regression Analysis
Reference
Chapter 3 Data Analytics for Environmental Engineering
3.1 Introduction to Environmental Engineering
3.2 Data Analysis in Environmental Engineering
3.3 Applications of Soft Computing Tools
3.4 Multiple Criteria Decision-Making (MCDM) Model
References
Chapter 4 Structural Engineering: Trends, Applications, and Advances
4.1 Overview of Structural Engineering
4.2 Need of Data Science in Structural Engineering
4.3 Current Trends and Applications of Data Science in Structural Engineering
4.4 Application of AI in Concrete Technology
4.5 Conclusion and Future Scope
References
Chapter 5 Application of Data Science in Transportation Systems
5.1 Introduction to Transportation Engineering
5.2 Data Analytics in Transportation Industry
5.3 Applications of Data Analytics in Transportation Planning and Management
5.4 Boom Bike-Sharing Demand Case Study
References
Appendix –
Chapter 6 Data Analytics for Water Resource Engineering
6.1 Introduction to Water Resource Engineering
6.2 Role of Big Data in Water Resources
6.3 Advanced Computational Intelligence Techniques in Water Resource Management
6.4 Predictive Models
6.5 Applications of Data Analytics in Water Resource Engineering
6.6 Case Study on Identification of Potential Groundwater Recharge Zones and Suitable Locations for Appropriate Artificial Recharge Structures Using Remote Sensing and GIS Technology
References
Chapter 7 Data Analysis in Geomatics
7.1 Introduction
7.2 Adjustment of Survey Measurement
7.3 Data Analysis in Satellite-Based Positioning System
7.4 Geospatial Analysis
7.5 Conclusion
References
Chapter 8 Conclusions
8.1 Summary
8.2 Business Intelligence
8.3 Research Openings and Future Outlook
Index

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Data science for civil engineering : a beginner's guide 이용현황 표 - 등록번호, 청구기호, 권별정보, 자료실, 이용여부로 구성 되어있습니다.
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0003075477 624.0285 -A24-2 [서울관] 인문자연과학자료실(열람신청 후 1층 대출대) 이용가능

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알라딘제공

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.



This book explains use of data science-based techniques for modelling and providing optimal solutions to complex problems in civil engineering. It deals with the basics of data science and essential mathematics and covers pertinent applications in structural and environmental engineering, construction management, and transportation.

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