Machine Learning Applications in Civil Engineering
- 1st Edition - September 29, 2023
- Imprint: Elsevier
- Author: Kundan Meshram
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 5 3 6 4 - 8
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 5 3 6 3 - 1
Machine Learning Applications in Civil Engineering discusses machine learning and deep learning models for different civil engineering applications. These models work for stochasti… Read more
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Request a sales quoteMachine Learning Applications in Civil Engineering discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods wherein internal processing is done using randomized prototypes. The book explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency. It introduces Machine Learning and its applications to different Civil Engineering tasks, including Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies.
Using this book, civil engineering students and researchers can deep dive into Machine Learning, and identify various solutions to practical Civil Engineering tasks.
- Introduces various ML models for Civil Engineering Applications that will assist readers in their analysis of design and development interfaces for building these applications
- Reviews different lacunas and challenges in current models used for Civil Engineering scenarios
- Explores designs for customized components for optimum system deployment
- Explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency
Students who would like to understand about ML in Civil Engineering, Researchers who want to explore various machine learning models for catering to different fields of Civil Engineering, Students who want to learn about basics of machine learning, and their real-time use-cases, Civil Engineering experts who want to identify & explore issues in their current designs, and solve them via machine learning methods, Engineers who want to learn about problem solving via use of deep learning techniques, Construction agencies that want to explore different use cases of machine learning for planning and redevelopment
- Cover image
- Title page
- Table of Contents
- Copyright
- Preface
- 1. Introduction to machine learning for civil engineering
- Abstract
- 1.1 Introduction to machine learning for civil engineering
- 1.2 What is machine learning and how can it be useful for optimization of civil engineering applications?
- 1.3 Use-case based review analysis of machine learning models for optimization of construction speed
- 1.4 Optimization of civil engineering tasks via machine learning-based system designs
- 1.5 Use of machine learning for different civil engineering areas
- References
- 2. Basic machine learning models for data pre-processing
- Abstract
- 2.1 Introduction
- 2.2 Data sources in civil engineering applications
- 2.3 Introduction to machine learning-based preprocessing models
- 2.4 Use of filtered signals for solving real-time civil engineering project
- References
- 3. Use of machine learning models for data representation
- Abstract
- 3.1 Introduction
- 3.2 What is data representation?
- 3.3 Data representation for civil engineering
- 3.4 Different machine learning methods for representing data for classification and postprocessing applications
- References
- 4. Introduction to classification models for civil engineering applications
- Abstract
- 4.1 Introduction
- 4.2 What is classification and how can it be used to optimize civil engineering applications?
- 4.3 Use case for geotechnical engineering
- 4.4 Use case for structural engineering applied to 3D building information modeling
- 4.5 Use case for water resources engineering
- 4.6 Use case for environmental parameter classifications
- 4.7 Use case for structural health monitoring system with structural design and analysis
- 4.8 Use case for remote sensing geometric information system applications
- References
- 5. Classification models for practical deployment in different civil engineering applications
- Abstract
- 5.1 Introduction
- 5.2 Introduction to k-nearest neighbors, random forests, naive Bayes, logistic regression, multiple-layered perceptron, and fuzzy logic models
- 5.3 Classification based on these models as applied to real time applications
- References
- 6. Advanced classification models for different civil engineering applications
- Abstract
- 6.1 Introduction to convolutional neural networks
- 6.2 Advantages of convolutional neural networks over traditional methods
- 6.3 Issues with convolutional neural networks when applied to civil engineering tasks
- 6.4 Applications of convolutional neural networks for different fields of civil engineering
- References
- 7. Advanced classification models II: extensions to convolutional neural networks
- Abstract
- 7.1 Introduction to recurrent neural networks
- 7.2 Long short-term memory
- 7.3 Gated recurrent units
- 7.4 Real-time applications of recurrent neural networks to civil engineering tasks
- 7.5 A use case of geographic information system application and its solutions with different deep learning models
- References
- 8. Bioinspired computing models for civil engineering
- Abstract
- 8.1 Introduction to bioinspired computing for optimization
- 8.2 Role of optimization in civil engineering
- 8.3 Different bioinspired models and their applications to solving traffic issues
- References
- 9. Reinforcement learning methods and role of internet of things in civil engineering applications
- Abstract
- 9.1 What is reinforcement learning?
- 9.2 Introduction to internet of things for civil engineering
- 9.3 Use of reinforcement learning for low-power internet of things-based civil engineering applications
- References
- 10. Solution to real time civil engineering tasks via machine learning
- Abstract
- 10.1 Introduction
- 10.2 Case study 1: use of drones for construction monitoring and their management via machine learning
- 10.3 Case study 2: conservation of water resources via bioinspired optimizations
- 10.4 Case study 3: reduction of greenhouse effect via use of recommendation models
- References
- Index
- Edition: 1
- Published: September 29, 2023
- Imprint: Elsevier
- No. of pages: 218
- Language: English
- Paperback ISBN: 9780443153648
- eBook ISBN: 9780443153631
KM
Kundan Meshram
Dr. Kundan Meshram is currently working as Assistant Professor, in the Department of Civil Engineering, at Guru Ghasidas Vishwavidyalaya (A Central University) Bilaspur (C.G.), India. He has received Ph.D. (Civil Engineering) from Maulana Azad National Institute of Technology Bhopal, India in 2016. His main research interest includes Pavement Material Characterization, Pavement Performance and Maintenance, Transportation Geotechnics, Road Safety, and Multimodal Transportation Systems. He has 05 patent and published 2 books, 3 book chapters and more 40 research papers in various International/National Journals, and Proceedings of reputed International/ National Conferences. He was awarded International Innovative Researcher in Civil Engineering, RULA Peace Award in 2019 and the CPWD Medal and Best Paper Award from the Indian Road Congress, for his paper ‘Pavement Deterioration Modeling for Low Volume Roads’ in 2015.
Affiliations and expertise
Assistant Professor, Department of Civil Engineering, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, Chattisgarh, IndiaRead Machine Learning Applications in Civil Engineering on ScienceDirect