作者
Jui-Sheng Chou, Thi-Phuong-Trang Pham, Thi-Kha Nguyen, Anh-Duc Pham, Ngoc-Tri Ngo
发表日期
2020/3
期刊
Soft Computing
卷号
24
期号
5
页码范围
3393-3411
出版商
Springer Berlin Heidelberg
简介
The shear strength of reinforced concrete (RC) beams is critical in the design of structural members. Developing an effective mathematical method for accurately estimating shear strength of RC beams is beneficial for civil engineers. This work presents a hybrid artificial intelligent (AI) model for effectively predicting the shear strength of various types of RC beam. The hybrid AI model was developed by integrating an optimization algorithm [smart firefly algorithm (SFA)] and machine learning [least squares support vector regression (LSSVR)], in which the SFA was used to optimize the hyperparameters of LSSVR, improving its predictive accuracy. Three large datasets were used to train and test the hybrid AI model in predicting shear strength of RC beams. The predictive accuracy of the hybrid AI model was compared comprehensively with those of single AI models, ensemble AI models, and empirical methods. The …
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