Neural Networks Applicability for Design of Reinforced Concrete Sections for Bending

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Krasimir Boshnakov, V. Yakov
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引用次数: 0

Abstract

Solving engineering design tasks requires the use of analytical formulas and dependencies. The direct inclusion of mathematical expressions in the artificial neural network (ANN) is not possible. This research studies the possibility of applying the neural networks method for designing of single or double-side reinforced concrete sections. A Visual Basic for Applications (VBA) macro was developed in the MS Excel environment to solve the task of determining the required area of the reinforcement by given geometric dimensions and bending moment and applying classical analytical formulas for reinforced concrete sections design. The training of the pre-configured neural network is performed by approximately 34000 sets of matching input parameters. The presented results from the trained ANN are compared and analysed against the exact analytical solutions. The study presents an approach to the application of structural design calculations. The results suggest that the approach is applicable to more complicated structural design problems.
神经网络在钢筋混凝土弯曲截面设计中的适用性
解决工程设计任务需要使用分析公式和相关性。在人工神经网络中直接包含数学表达式是不可能的。本研究探讨了将神经网络方法应用于单面或双面钢筋混凝土截面设计的可能性。在MS Excel环境中开发了一个Visual Basic for Applications(VBA)宏,以解决通过给定的几何尺寸和弯矩确定钢筋所需面积的任务,并将经典分析公式应用于钢筋混凝土截面设计。通过大约34000组匹配的输入参数来执行预配置的神经网络的训练。将训练后的神经网络的结果与精确的分析解进行比较和分析。该研究提出了一种应用结构设计计算的方法。结果表明,该方法适用于更复杂的结构设计问题。
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来源期刊
TEM Journal-Technology Education Management Informatics
TEM Journal-Technology Education Management Informatics COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.20
自引率
14.30%
发文量
176
审稿时长
8 weeks
期刊介绍: TEM JOURNAL - Technology, Education, Management, Informatics Is a an Open Access, Double-blind peer reviewed journal that publishes articles of interdisciplinary sciences: • Technology, • Computer and informatics sciences, • Education, • Management
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