Neural networks for predicting properties of concretes with admixtures

W.P.S. Dias; S.P. Pooliyadda

首页> 外文期刊>Construction and Building Materials >Neural networks for predicting properties of concretes with admixtures

【24h】

Neural networks for predicting properties of concretes with admixtures

机译：神经网络预测掺合料混凝土的性能

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Backpropagation neural networks were used to predict the strength and slump of ready mixed concrete and high strength concrete, in which chemical admixtures and/or mineral additives were used. Although various data transforms were tried, it was found that models based on raw data gave the best results. When non-dimensional ratios were used, arranging the ratios such that their changes resulted in corresponding changes in the output (e.g. increases in ratios to cause increases in output values) improved network performance.

机译：反向传播神经网络用于预测预拌混凝土和高强度混凝土的强度和坍落度，其中使用了化学外加剂和/或矿物添加剂。尽管尝试了各种数据转换，但是发现基于原始数据的模型可以提供最佳结果。当使用无量纲比率时，安排比率以使它们的变化导致输出的相应变化（例如，比率增加以导致输出值增加）会改善网络性能。

著录项

来源
《Construction and Building Materials》 |2001年第7期|p.371-379|共9页
作者
W.P.S. Dias; S.P. Pooliyadda;
展开▼
作者单位

展开▼
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
中图分类建筑材料;
关键词
Backpropagation neural networks; Models; Concrete properties;

机译：反向传播神经网络;楷模;混凝土性能;

相似文献

外文文献
中文文献
专利

1. Evaluating and forecasting the initial and final setting times of self-compacting concretes containing mineral admixtures by neural network [J] . Erhan Gueneyisi, Mehmet Gesoglu, Erdogan OEzbay Materials and structures . 2009,第4期

机译：通过神经网络评估和预测含矿物掺合料的自密实混凝土的初始和最终凝固时间
2. Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria-Based Concrete [J] . Aref M. al-Swaidani, Waed T. Khwies Advances in civil engineering . 2018,第1期

机译：人工神经网络在预测火山灰骨水泥基混凝土力学性能和渗透性方面的适用性
3. Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria-Based Concrete [J] . al-Swaidani Aref M., Khwies Waed T. Advances in civil engineering . 2018,第PTa10期

机译：人工神经网络在预测火山灰骨水泥基混凝土力学性能和渗透性能方面的适用性
4. Prediction of Compressive Strength of Green Concrete with Admixtures Using Neural Networks [C] . Priyanka Singh, Partha Khaskil IEEE International Conference on Computing, Power and Communication Technologies . 2020

机译：基于神经网络的掺加料绿色混凝土抗压强度预测
5. Neural networking to model and predict properties of stabilized road base designs. [D] . Hensley, Timothy T. 2010

机译：神经网络可以对稳定的路基设计进行建模和预测。
6. Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks [O] . Marzena Kurpinska, Leszek Kułak 2019

机译：利用人工神经网络预测粒状膨胀玻璃灰骨料轻质混凝土的性能。
7. Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria-Based Concrete [O] . Aref M. al-Swaidani, Waed T. Khwies 2018

机译：人工神经网络的适用性预测火山孢子型混凝土机械和渗透性能

Neural networks for predicting properties of concretes with admixtures

摘要

著录项

相似文献

相关主题

期刊订阅