Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model

Joint Authors

Lei, Yawei
Huang, Jiandong
Duan, Tianhong
Zhang, Yi
Liu, Jiandong
Zhang, Jia

Source

Advances in Civil Engineering

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-12-29

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Civil Engineering

Abstract EN

Pervious concrete is an environmentally friendly material that improves water permeability, skid resistance, and sound absorption characteristics.

Permeability is the most important functional performance for the pervious concrete while limited studies have been conducted to predict permeability based on mix-design parameters.

This study proposed a method to combine the beetle antennae search (BAS) and random forest (RF) algorithm to predict the permeability of pervious concrete.

Based on the 36 samples designed in the laboratory and 4 key influencing variables, the permeability of pervious concrete can be obtained by varying mix-design parameters by RF.

BAS algorithm was used to tune the hyperparameters of RF, which were then verified by the so-called 10-fold cross-validation.

Furthermore, the model to combine the BAS and RF was validated by the correlation parameters.

The results showed that the hyperparameters of RF can be tuned by the BAS efficiently; the BAS can combine the conventional RF algorithm to construct the evolved model to predict the permeability of pervious concrete; the cement/aggregate ratio was the most significant variable to determine the permeability, followed by the coarse aggregate proportions.

American Psychological Association (APA)

Huang, Jiandong& Duan, Tianhong& Zhang, Yi& Liu, Jiandong& Zhang, Jia& Lei, Yawei. 2020. Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model. Advances in Civil Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1124462

Modern Language Association (MLA)

Huang, Jiandong…[et al.]. Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model. Advances in Civil Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1124462

American Medical Association (AMA)

Huang, Jiandong& Duan, Tianhong& Zhang, Yi& Liu, Jiandong& Zhang, Jia& Lei, Yawei. Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model. Advances in Civil Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1124462

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1124462