Machine 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.
1. 1. Introduction to machine learning for civil engineering - p. 1 2. 2. Basic machine learning models for data pre-processing - p. 17 3. 3. Use of machine learning models for data representation - p. 33 4. 4. Introduction to classification models for civil engineering applications - p. 51 5. 5. Classification models for practical deployment in different civil engineering applications - p. 71 6. 6. Advanced classification models for different civil engineering applications - p. 89 7. 7. Advanced classification models II: extensions to convolutional neural networks - p. 103 8. 8. Bioinspired computing models for civil engineering - p. 121 9. 9. Reinforcement learning methods and role of internet of things in civil engineering applications - p. 149 10. 10. Solution to real time civil engineering tasks via machine learning - p. 169 11. Index - p. 199
Machine 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.
1. 1. Introduction to machine learning for civil engineering - p. 1 2. 2. Basic machine learning models for data pre-processing - p. 17 3. 3. Use of machine learning models for data representation - p. 33 4. 4. Introduction to classification models for civil engineering applications - p. 51 5. 5. Classification models for practical deployment in different civil engineering applications - p. 71 6. 6. Advanced classification models for different civil engineering applications - p. 89 7. 7. Advanced classification models II: extensions to convolutional neural networks - p. 103 8. 8. Bioinspired computing models for civil engineering - p. 121 9. 9. Reinforcement learning methods and role of internet of things in civil engineering applications - p. 149 10. 10. Solution to real time civil engineering tasks via machine learning - p. 169 11. Index - p. 199
