Genetic Programming Based Formulation to Predict Compressive Strength of High Strength Concrete

IF 1 Q4 ENGINEERING, CIVIL
G. Abdollahzadeh, E. Jahani, Zahra Kashir
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引用次数: 12

Abstract

This study introduces, two models based on Gene Expression Programming (GEP) to predict compressive strength of high strength concrete (HSC). Composition of HSC was assumed simplified, as a mixture of six components (cement, silica fume, super-plastisizer, water, fine aggregate and coarse aggregate). The 28-day compressive strength value was considered the target of the prediction.  Data on 159 mixes were taken from various publications. The system was trained based on 80% training pairs chosen randomly from the data set and then tested using remaining 20% samples. Therefore it can be proven and illustrated that the GEP is a strong technique for the prediction of compressive strength amounts of HSC concerning to the outcomes of the training and testing phases compared with experimental outcomes illustrate that the.
基于遗传规划的高强混凝土抗压强度预测公式
介绍了两种基于基因表达式编程(GEP)的高强混凝土抗压强度预测模型。假定HSC的组成简化为六组分(水泥、硅灰、超塑剂、水、细骨料和粗骨料)的混合物。28天的抗压强度值被认为是预测的目标。159种混合物的数据来自不同的出版物。系统基于从数据集中随机选择的80%的训练对进行训练,然后使用剩余的20%样本进行测试。因此,可以证明和说明GEP是一种强有力的技术,用于预测HSC的抗压强度量,涉及到训练和测试阶段的结果,与实验结果相比,说明GEP是一种有效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.30
自引率
60.00%
发文量
0
审稿时长
47 weeks
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