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Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures [#498444]

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures
Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures
by Won-Kee Hong

English | 2023 | ISBN: 103232368X | 581 pages | True PDF EPUB | 69.75 MB


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.

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