Artificial Intelligence Applications for Sustainable Construction: Woodhead Publishing Series in Civil and Structural Engineering
Editat de Moncef L. Nehdi, Harish Chandra Arora, Krishna Kumar, Robertas Damaševicius, Aman Kumaren Limba Engleză Paperback – 16 feb 2024
- 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
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Specificații
ISBN-13: 9780443131912
ISBN-10: 0443131910
Pagini: 438
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
Seria Woodhead Publishing Series in Civil and Structural Engineering
ISBN-10: 0443131910
Pagini: 438
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
Seria Woodhead Publishing Series in Civil and Structural Engineering
Cuprins
1. Artificial Intelligence in Civil Engineering: An Immersive View
2. Application of Artificial Intelligence in Sustainable Construction: Secret Eye towards Latest Civil Engineering Techniques
3. Machine Learning (ML) in Sustainable Composite Building Materials to Reduce Carbon Emission
4. Application of Machine Learning Models for the Compressive Strength Prediction of Concrete with Glass Waste Powder
5. AI-based Structural Health Monitoring Systems
6. Application of Ensemble Learning in Rock Mass Rating for Tunnel Construction
7. AI-based Framework for Construction 4.0: A Case Study for Structural Health Monitoring
8. Practical Prediction of Ultimate Axial Strain and Peak Axial Stress of FRP-Confined Concrete using Hybrid ANFIS-PSO Models
9. Prediction of Long-Term Dynamic Responses of a Heritage Masonry Building under Thermal Effects by Automated Kernel-Based Regression Modeling
10. A Comprehensive Review on Application of Artificial Intelligence in Construction Management using Science Mapping Approach
11. Textile Reinforced Mortar-Masonry Bond Strength Calibration Using Machine Learning Methods
12. Forecasting the compressive strength of FRCM-strengthened RC columns with Machine learning algorithms
13. Assessment of Shear Capacity of FRP-Reinforced Concrete Beam Without Stirrup: Machine Learning Approach
14. Estimating the Load Carrying Capacity of Reinforced Concrete Beam-Column Joints via Soft Computing Techniques
15. Global Seismic Damage Assessment of RC Framed Buildings using Machine Learning Techniques
2. Application of Artificial Intelligence in Sustainable Construction: Secret Eye towards Latest Civil Engineering Techniques
3. Machine Learning (ML) in Sustainable Composite Building Materials to Reduce Carbon Emission
4. Application of Machine Learning Models for the Compressive Strength Prediction of Concrete with Glass Waste Powder
5. AI-based Structural Health Monitoring Systems
6. Application of Ensemble Learning in Rock Mass Rating for Tunnel Construction
7. AI-based Framework for Construction 4.0: A Case Study for Structural Health Monitoring
8. Practical Prediction of Ultimate Axial Strain and Peak Axial Stress of FRP-Confined Concrete using Hybrid ANFIS-PSO Models
9. Prediction of Long-Term Dynamic Responses of a Heritage Masonry Building under Thermal Effects by Automated Kernel-Based Regression Modeling
10. A Comprehensive Review on Application of Artificial Intelligence in Construction Management using Science Mapping Approach
11. Textile Reinforced Mortar-Masonry Bond Strength Calibration Using Machine Learning Methods
12. Forecasting the compressive strength of FRCM-strengthened RC columns with Machine learning algorithms
13. Assessment of Shear Capacity of FRP-Reinforced Concrete Beam Without Stirrup: Machine Learning Approach
14. Estimating the Load Carrying Capacity of Reinforced Concrete Beam-Column Joints via Soft Computing Techniques
15. Global Seismic Damage Assessment of RC Framed Buildings using Machine Learning Techniques