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Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures.

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures.

・ISBN 978-1-032-32369-5 paper GB£ 62.99

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お気に入り
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9781003314684
著者・編者Hong, Won-Kee,
出版社 (CRC Press, UK)
出版年月2024
ページ数564 pp.
言語ENG
ニュース番号<A03-64703>

解説

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.