AI-Based Optimized Design of Structural Frames - With Application to Practical Building Designs

This book introduces an auto-design-based optimization for building frames using an artificial neural networks (ANN)-based Lagrange method and genetic algorithms (GAs), and consistent with codes of practice. It is heavily illustrated with color figures and tables.

Inhaltsverzeichnis

1. Introduction to optimizations of structural frames. 2. An auto-design for optimizing RC frames using the ANN-based Hong-Lagrange algorithm. 3. An auto-design for optimizing prestressed frames using the ANN-based Hong-Lagrange algorithm. 4. An auto-design for optimizing steel frames using the ANN-based Hong-Lagrange algorithm. 5. A new GA using mutations with dynamic ranges and a probability-based natural selection method to optimize precast beams. 6. AI-based optimizations of RC and PT frames (AI-FRT) using penalty-based genetic algorithm with probabilistic-based natural selections (PPD-GA) using dynamic mutations.

Über den Autor / die Autorin

Won¿Kee Hong is a professor of Architectural Engineering at Kyung Hee University, Republic of Korea. He has more than 35 years of professional experience in structural and construction engineering, having worked for Englekirk and Hart, USA; Nihon Sekkei, Japan; and Samsung Engineering and Construction, Korea. He has published more than 20 international papers in the field of AI¿based structural designs including building frames. He is the author of several books including Hybrid Composite Precast Systems (Elsevier), Artificial Intelligence¿Based Design of Reinforced Concrete Structures (Elsevier), Artificial Neural Network¿based Optimized Design of Reinforced Concrete Structures (CRC Press, Taylor & Francis Group) and Artificial Neural Network¿based Prestressed Concrete and Composite Structures (CRC Press, Taylor & Francis Group).

Zusammenfassung

This book introduces an auto-design-based optimization for building frames using an artificial neural networks (ANN)-based Lagrange method and genetic algorithms (GAs), and consistent with codes of practice. It is heavily illustrated with color figures and tables.

Produktdetails

• Autoren: Won‐Kee Hong
• Verlag: Taylor and Francis
• Sprache: Englisch
• Produktform: Fester Einband
• Erschienen: 16.10.2024
• EAN: 9781032536811
• ISBN: 978-1-03-253681-1
• Seiten: 582
• Gewicht: 1238 g
• Illustration: schwarz-weiss Illustrationen, farbige Illustrationen, Zeichnungen, schwarz-weiss, Zeichnungen, farbig, Tabellen, schwarz-weiss
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Technik > Bau- und Umwelttechnik; Sozialwissenschaften, Recht,Wirtschaft > Wirtschaft > Einzelne Wirtschaftszweige, Branchen; Data Mining, TECHNOLOGY & ENGINEERING / Civil / General, TECHNOLOGY & ENGINEERING / Structural, Structural engineering, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Data Science / Neural Networks, Neural networks and fuzzy systems, Neural networks & fuzzy systems