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Predicting the Poisson Ratio of Lightweight Concretes using Artificial Neural Network

机译:利用人工神经网络预测轻质混凝土的泊松比

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摘要

Artificial neural network is generally information processing system and a computer program that imitates human brain neural network system. By entering the information from outside, artificial neural network can be trained on examples related to a problem, so that modeling of the problem is provided. In this study, compressive strength, Poisson ratio of the lightweight concrete specimens, which have different natural lightweight aggregates, were modeled with artificial neural network. The data which were provided by artificial neural network model were compared with the data obtained from experimental study and a good agreement was determined between the results.
机译:人工神经网络通常是信息处理系统和模仿人脑神经网络系统的计算机程序。通过从外部输入信息,可以在与问题相关的示例上训练人工神经网络,从而提供问题的建模。在这项研究中,使用人工神经网络对具有不同天然轻质骨料的轻质混凝土试样的抗压强度,泊松比进行建模。将由人工神经网络模型提供的数据与从实验研究中获得的数据进行比较,结果之间取得了很好的一致性。

著录项

  • 来源
    《Acta Physica Polonica》 |2015年第2b期|B184-B186|共3页
  • 作者单位

    Suleyman Demirel Univ, Nat & Ind Bldg Mat Applicat & Res Ctr, TR-32200 Isparta, Turkey;

    Suleyman Demirel Univ, Nat & Ind Bldg Mat Applicat & Res Ctr, TR-32200 Isparta, Turkey;

    Suleyman Demirel Univ, Tech Sci Vocat Sch, Dept Construct, Isparta, Turkey;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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