In this paper, optimal designs for precast beams were determined using a genetic algorithm.
Two new features for enhancing genetic algorithms were developed in the present study …

This study proposes artificial neural networks (ANNs) that can solve structural engineering
problems in general and design ductile concrete beams in particular. ANNs demonstrating a …

This study aims to develop artificial neural networks (ANNs)-based forward Lagrange
networks optimizing ductile doubly reinforced concrete (RC) beams. Cost (CIb) of materials …

Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures
introduces AI-based Lagrange optimization techniques that can enable more rational …

This study proposes an artificial neural network for a design of reinforced concrete (RC)
columns for structural engineers who are interested in performing reverse designs, exploring …

ABSTRACT Chained Training Scheme (CTS) and Chained training scheme with Revised
Sequence (CRS) were proposed to train artificial neural networks (ANNs) to design doubly …

In the structural engineering field, multi-objective optimization is a difficult task as demands
of objective functions in structural designs are sometimes conflicting, such as costs and …

Multi-objective optimization (MOO) is always a challenging issue for engineers in the field of
structural engineering, where several objective functions must be satisfied under equality …

Design of steel-reinforced concrete (SRC) beams can be a lengthy process, and
understanding how design parameters as many as over 26 influence each other can be …

The present paper introduces a practical and convenient artificial intelligence-based design
approach for doubly reinforced concrete (RC) beams. Completed designs are automatically …