Version 1
: Received: 31 October 2023 / Approved: 31 October 2023 / Online: 1 November 2023 (03:12:46 CET)
Version 2
: Received: 29 December 2023 / Approved: 29 December 2023 / Online: 2 January 2024 (02:04:15 CET)
Argha, D.B.P.; Ahmed, M.A. A Machine Learning Approach to Understand the Impact of Temperature and Rainfall Change on Concrete Pavement Performance Based on LTPP Data. SVU-International Journal of Engineering Sciences and Applications 2024, 5, 150–155, doi:10.21608/svusrc.2023.250899.1164.
Argha, D.B.P.; Ahmed, M.A. A Machine Learning Approach to Understand the Impact of Temperature and Rainfall Change on Concrete Pavement Performance Based on LTPP Data. SVU-International Journal of Engineering Sciences and Applications 2024, 5, 150–155, doi:10.21608/svusrc.2023.250899.1164.
Argha, D.B.P.; Ahmed, M.A. A Machine Learning Approach to Understand the Impact of Temperature and Rainfall Change on Concrete Pavement Performance Based on LTPP Data. SVU-International Journal of Engineering Sciences and Applications 2024, 5, 150–155, doi:10.21608/svusrc.2023.250899.1164.
Argha, D.B.P.; Ahmed, M.A. A Machine Learning Approach to Understand the Impact of Temperature and Rainfall Change on Concrete Pavement Performance Based on LTPP Data. SVU-International Journal of Engineering Sciences and Applications 2024, 5, 150–155, doi:10.21608/svusrc.2023.250899.1164.
Abstract
Climate change is one of the most concerning global issues and has the potential to influence every aspect of human life. Like different components of society, it can impose significant adverse impacts on pavement infrastructure. Although several research efforts have focused on studying the effects of climate change on natural and built systems, its impact on pavement performance has not been studied extensively. Due to the weather effect the lifetime of pavement is getting lower on the other hand maintenance cost is getting higher and higher. The data has been collected from LTTP website and as a site The State of Texas has been considered. The primary objective of this project is to quantify the effect of temperature as well as precipitation changes on pavement response and performance prediction using the ARIMA model and develop a logistic regression model to analyze the forecast data.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Md Ashik Ahmed
Commenter's Conflict of Interests: Author