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.
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.
Won¿Kee Hong is a professor of architectural engineering at Kyung Hee University, South Korea. He has more than 35 years of professional experience in structural and construction engineering, having worked for Englekirk and Hart, USA; Nihhon Sekkei, Japan; and Samsung Engineering and Construction, Korea. He is the author of Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures and Artificial Neural Network-based Prestressed Concrete and Composite Structures, also published by CRC Press.
Inhaltsangabe
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.
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.
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