Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis
المؤلفون المشاركون
Sirin, Okan
Mamun, A. A.
Arifuzzaman, Md
Gazder, Uneb
Alam, Md Shah
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-7، 7ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-08-15
دولة النشر
مصر
عدد الصفحات
7
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1129408
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر