Forecast flexural strength of pervious concrete by SVR

被引:2
|
作者
Bin Ahmed, Farabi [1 ]
Mitu, Sadia Mannan [2 ]
Biswas, Rajib Kumar [3 ]
Ahsan, Khan Abid [1 ]
Mim, Sabrina Mostarin [1 ]
Ahmed, Saif [1 ]
机构
[1] Ahsanullah Univ Sci & Technol, Civil Engn, Tejgaon Ind Area, 141 & 142 Love Rd, Dhaka 1208, Bangladesh
[2] Natl Univ Malaysia, Civil Engn, Bangi, Malaysia
[3] Tokyo Inst Technol, Civil & Environm Engn, Meguro Ku, 2-12-1-M1-21 O Okayama, Tokyo 1528552, Japan
关键词
Compressive strength; Flexural strength; Power regression analysis; Support vector machine; Kernel radial basis function regression analysis;
D O I
10.1016/j.matpr.2021.01.832
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
For the development of construction technology, pervious concrete is vastly using in road infrastructure. Pervious concrete has a strong drainage ability that can recharge groundwater, made by the coarse aggregate, water, and cement with little fine aggregate or without fine aggregate. The compressive and flexural strengths of pervious concrete are vital parameters to identify the concrete quality and also necessary in the process of analysis and design of a concrete infrastructure. This research represents a system for forecasting the flexural strength obtained from the compressive strength (0 up to 30 MPa) of concrete cube and cylinder types specimens by support vector regression (SVR) for both 7 and 28 days. Experimental data from various literature have been collected to formulate the model. It appears that the relationship between the compressive strength and flexural strength of pervious concrete is non-linear. The linear models developed with limited lab test found ineffective when they are subjected to wide range of data set for flexural strength prediction. In this study, all compared models and developing model's effectiveness are examined based on R2, RMSE, MAPE, MSE, and IAE parameters for both 7- and 28-days specimens. (c) 2021 Elsevier Ltd. All rights reserved. Second International Conference on Aspects of Materials Science and Engineering (ICAMSE 2021).
引用
收藏
页码:5277 / 5284
页数:8
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