Computational Response Control in Structures
Theory, Optimization, and Artificial Intelligence Applications
- 1st Edition - April 1, 2027
- Latest edition
- Editor: Salar Farahmand-Tabar
- Language: English
Computational Response Control in Structures: Theory, Optimization, and Artificial Intelligence Application integrates theory, optimization techniques, and artificial intell… Read more
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Description
Description
Computational Response Control in Structures: Theory, Optimization, and Artificial Intelligence Application integrates theory, optimization techniques, and artificial intelligence (AI) applications to provide a thorough understanding of various control methods, including passive, semi-active, active, and hybrid, as well as other specific structural types such as low-rise and high-rise buildings, bridges, and other structures. The role of AI in structural control, optimization techniques for enhancing control performance, and the emergence of smart structures are each discussed as well, with a focus on combining theoretical foundations with practical applications, showcasing case studies and real-world examples to illustrate the implementation of control systems.
How machine learning models can be leveraged to improve the performance of metaheuristic techniques is outlined, and the integration of AI and optimization techniques into structural control is highlighted, equipping readers with the knowledge and tools needed to develop efficient control strategies for a wide range of structures and enabling them to address the complexities and uncertainties encountered in structural control applications.
How machine learning models can be leveraged to improve the performance of metaheuristic techniques is outlined, and the integration of AI and optimization techniques into structural control is highlighted, equipping readers with the knowledge and tools needed to develop efficient control strategies for a wide range of structures and enabling them to address the complexities and uncertainties encountered in structural control applications.
Key features
Key features
- Provides fundamental knowledge in structural control with a focus on the integration of theory, optimization techniques, and artificial intelligence (AI)
- Covers passive, semi-active, active, and hybrid control, as well as specific structural types such as low-rise and high-rise buildings, bridges, and other structures
- Discusses the role of AI in structural control, optimization techniques for enhancing control performance, and the emergence of smart structures
Readership
Readership
Researchers and advanced grad students in mechanical engineering, civil engineering, structural engineering
Table of contents
Table of contents
1. Classical Control Methods for Structures: A State-of-the-Art Review
2. Passive Control Methods of Structures: A State-of-the-Art Review
3. Semi-Active Control Methods of Structures: A State-of-the-Art Review
4. Active Control Methods of Structures: A State-of-the-Art Review
5. Hybrid Control Methods of Structures: A State-of-the-Art Review
6. Optimization and AI Techniques in Structural Control
7. Atomic Orbital Search with Opposition-Based Learning for Optimal Passive Control of Simplified Moment Frames with Various Base Isolation Systems
8. Achieving Optimum Control with Passive MTMD Distribution in Tall Shear Frame Buildings via Nelder-Mead-Assisted Charged System Search
9. Pattern Configuration of Viscous Damper to Enhance Seismic Resilience of Shear Frames with Soil-Structure Interaction Using Upgraded Colliding Body Optimization
10. Inverse TSK Model to Predict and Design Optimum Control System in Nonlinear Building Based on Particle Swarm Clustered Optimizer
11. Optimum Mega Bracing Fuzzy Control with Magnetorheological Damper in Tall Buildings Through Improved Social Mimic Optimizer
12. Achieving Seismic Resilience in Shear Frames Through Fuzzy-Based Semi-Active Tuned Mass Damper (STMD) Control and Machine Learning Guided Cross Entropy Optimization
13. Optimum Structural Vibration Control in Real-Sized Steel Buildings Using Intelligent Active Control Systems and Energy Valley Optimizer
14. Seismic Response Reduction of Non-Linear Base Isolation System Using a Neural Network Driven Active Mass Damper
15. Chaos-Based Optimization Methods for Response Control of Steel Structures
16. Structural Control in Offshore Structures with Optimum Vertically Distributed TMDs Using Machine Learning Based Brain Storm Optimization
17. Computational Modeling for Innovative Control Systems
2. Passive Control Methods of Structures: A State-of-the-Art Review
3. Semi-Active Control Methods of Structures: A State-of-the-Art Review
4. Active Control Methods of Structures: A State-of-the-Art Review
5. Hybrid Control Methods of Structures: A State-of-the-Art Review
6. Optimization and AI Techniques in Structural Control
7. Atomic Orbital Search with Opposition-Based Learning for Optimal Passive Control of Simplified Moment Frames with Various Base Isolation Systems
8. Achieving Optimum Control with Passive MTMD Distribution in Tall Shear Frame Buildings via Nelder-Mead-Assisted Charged System Search
9. Pattern Configuration of Viscous Damper to Enhance Seismic Resilience of Shear Frames with Soil-Structure Interaction Using Upgraded Colliding Body Optimization
10. Inverse TSK Model to Predict and Design Optimum Control System in Nonlinear Building Based on Particle Swarm Clustered Optimizer
11. Optimum Mega Bracing Fuzzy Control with Magnetorheological Damper in Tall Buildings Through Improved Social Mimic Optimizer
12. Achieving Seismic Resilience in Shear Frames Through Fuzzy-Based Semi-Active Tuned Mass Damper (STMD) Control and Machine Learning Guided Cross Entropy Optimization
13. Optimum Structural Vibration Control in Real-Sized Steel Buildings Using Intelligent Active Control Systems and Energy Valley Optimizer
14. Seismic Response Reduction of Non-Linear Base Isolation System Using a Neural Network Driven Active Mass Damper
15. Chaos-Based Optimization Methods for Response Control of Steel Structures
16. Structural Control in Offshore Structures with Optimum Vertically Distributed TMDs Using Machine Learning Based Brain Storm Optimization
17. Computational Modeling for Innovative Control Systems
Product details
Product details
- Edition: 1
- Latest edition
- Published: April 1, 2027
- Language: English
About the editor
About the editor
SF
Salar Farahmand-Tabar
Salar Farahmand-Tabar is a structural engineering researcher and university lecturer. His research interests include computational mechanics, structural optimization, bridge engineering, and more. He strives to contribute to structure advancements through the practical use of computational intelligence and optimization in the field of computational mechanics, using programming languages such as MATLAB® and Python. He has published papers in international journals in the field, and collaborates with prestigious journals as a reviewer.
Affiliations and expertise
University Lecturer, Department of Civil Engineering, Faculty of Engineering, University of Zanjan, Iran