Artificial Neural Network-Based Optimized Design of Reinforced Concrete Structures

By Won‐Kee Hong

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures

introduces AI-based Lagrange optimization techniques that can enable more rational engineering

decisions for concrete structures while conforming to codes of practice. It shows

how objective functions including cost, CO2 emissions, and structural weight of concrete

structures are optimized either separately or simultaneously while satisfying constraining

design conditions using an ANN-based Lagrange algorithm. Any design target can be

adopted as an objective function. Many optimized design examples are verified by both

conventional structural calculations and big datasets.

- Uniquely applies the new powerful tools of AI to concrete structural design and

optimization

- Multi-objective functions of concrete structures optimized either separately or

simultaneously

- Design requirements imposed by codes are automatically satisfied by constraining

conditions

- Heavily illustrated in color with practical design examples

The book suits undergraduate and graduate students who have an understanding of collegelevel

calculus and will be especially beneficial to engineers and contractors who seek to

optimize concrete structures.

• Format: Hardcover
• Language: English
• ISBN: 103232368X
• ISBN13: 9781032323688
• Release Date: January 2023
• Publisher: CRC Press
• Length: 564 Pages