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

<p>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 prop...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Md Arifuzzaman (11471123) (author)
مؤلفون آخرون: Uneb Gazder (13025406) (author), Md Shah Alam (4806219) (author), Okan Sirin (14603304) (author), Abdullah Al Mamun (14152077) (author)
منشور في: 2019
الموضوعات:
الوسوم: إضافة وسم
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author Md Arifuzzaman (11471123)
author2 Uneb Gazder (13025406)
Md Shah Alam (4806219)
Okan Sirin (14603304)
Abdullah Al Mamun (14152077)
author2_role author
author
author
author
author_facet Md Arifuzzaman (11471123)
Uneb Gazder (13025406)
Md Shah Alam (4806219)
Okan Sirin (14603304)
Abdullah Al Mamun (14152077)
author_role author
dc.creator.none.fl_str_mv Md Arifuzzaman (11471123)
Uneb Gazder (13025406)
Md Shah Alam (4806219)
Okan Sirin (14603304)
Abdullah Al Mamun (14152077)
dc.date.none.fl_str_mv 2019-08-15T21:00:00Z
dc.identifier.none.fl_str_mv 10.1155/2019/3183050
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Modelling_of_Asphalt_s_Adhesive_Behaviour_Using_Classification_and_Regression_Tree_CART_Analysis/22082777
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Mathematical sciences
Pure mathematics
General Mathematics
General Medicine
General Neuroscience
General Computer Science
dc.title.none.fl_str_mv Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p>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. </p> <h2>Other information</h2> <p>Published in: Computational Intelligence and Neuroscience<br> License: <a href="http://creativecommons.org/licenses/by/4.0" target="_blank">http://creativecommons.org/licenses/by/4.0</a><br> See article on publisher's website: <a href="http://dx.doi.org/10.1155/2019/3183050" target="_blank">http://dx.doi.org/10.1155/2019/3183050</a> </p>
eu_rights_str_mv openAccess
id Manara2_2bf7232e5069510508b0f558a91495dc
identifier_str_mv 10.1155/2019/3183050
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/22082777
publishDate 2019
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spelling Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) AnalysisMd Arifuzzaman (11471123)Uneb Gazder (13025406)Md Shah Alam (4806219)Okan Sirin (14603304)Abdullah Al Mamun (14152077)Mathematical sciencesPure mathematicsGeneral MathematicsGeneral MedicineGeneral NeuroscienceGeneral Computer Science<p>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. </p> <h2>Other information</h2> <p>Published in: Computational Intelligence and Neuroscience<br> License: <a href="http://creativecommons.org/licenses/by/4.0" target="_blank">http://creativecommons.org/licenses/by/4.0</a><br> See article on publisher's website: <a href="http://dx.doi.org/10.1155/2019/3183050" target="_blank">http://dx.doi.org/10.1155/2019/3183050</a> </p>2019-08-15T21:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1155/2019/3183050https://figshare.com/articles/journal_contribution/Modelling_of_Asphalt_s_Adhesive_Behaviour_Using_Classification_and_Regression_Tree_CART_Analysis/22082777CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/220827772019-08-15T21:00:00Z
spellingShingle Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
Md Arifuzzaman (11471123)
Mathematical sciences
Pure mathematics
General Mathematics
General Medicine
General Neuroscience
General Computer Science
status_str publishedVersion
title Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
title_full Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
title_fullStr Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
title_full_unstemmed Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
title_short Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
title_sort Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
topic Mathematical sciences
Pure mathematics
General Mathematics
General Medicine
General Neuroscience
General Computer Science