Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART)‎ Analysis

Joint Authors

Sirin, Okan
Mamun, A. A.
Arifuzzaman, Md
Gazder, Uneb
Alam, Md Shah

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-08-15

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Biology

Abstract EN

The modification by polymers and nanomaterials can significantly improve different properties of asphalt.

However, during the service life, the oxidation affects the constituents of modified asphalt and subsequently results in deviation from the desired properties.

One of the important properties affected due to oxidation is the adhesive properties of modified asphalt.

In this study, the adhesive properties of asphalt modified with the polymers (styrene-butadiene-styrene and styrene-butadiene) and carbon nanotubes were investigated.

Asphalt samples were aged in the laboratory by simulating the field conditions, and then adhesive properties were evaluated by different tips of atomic force microscopy (AFM) following the existing functional group in asphalt.

Finally, a predictive modelling and machine learning technique called the classification and regression tree (CART) was used to predict the adhesive properties of modified asphalt subjected to oxidation.

The parameters that affect the behaviour of asphalt have been used to predict the results using the CART.

The results obtained from CART analysis were also compared with those from the regression model.

It was observed that the CART analysis shows more explanatory relationships between different variables.

The model can predict accurately the adhesive properties of modified asphalts considering the real field oxidation and chemistry of asphalt at a nanoscale.

American Psychological Association (APA)

Arifuzzaman, Md& Gazder, Uneb& Alam, Md Shah& Sirin, Okan& Mamun, A. A.. 2019. Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1129408

Modern Language Association (MLA)

Arifuzzaman, Md…[et al.]. Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-7.
https://search.emarefa.net/detail/BIM-1129408

American Medical Association (AMA)

Arifuzzaman, Md& Gazder, Uneb& Alam, Md Shah& Sirin, Okan& Mamun, A. A.. Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-7.
https://search.emarefa.net/detail/BIM-1129408

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1129408