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Can I read Creating Rutting Prediction Models through Machine Learning Techniques Utilizing the Long-Term Pavement Performance Database on EtoBox?
Creating Rutting Prediction Models through Machine Learning Techniques Utilizing the Long-Term Pavement Performance Database by Ali Juma Alnaqbi; Waleed Zeiada; Ghazi G. Al-Khateeb; Khaled Hamad; Samer Barakat is a Environmental Science article available to read on EtoBox.
What is Creating Rutting Prediction Models through Machine Learning Techniques Utilizing the Long-Term Pavement Performance Database about?
Over time, roads undergo deterioration caused by various factors such as traffic loads, climate conditions, and material properties. Considering the substantial global investments in road construction, it is crucial to periodically assess and implement maintenance and rehabilitation (M and R) plans to ensure the network’s acceptable level of service. An integral component of the M and R plan involves utilizing performance prediction models, especially for rutting distress, a significant issue in asphalt pavement. This study aimed to develop rutting prediction models using data from the Long-Term Pavement Performance (LTPP) database, employing several machine learning techniques such as regression tree (RT), support vector machine (SVM), ensembles, Gaussian process regression (GPR), and Artificial Neural Network (ANN). These techniques are well-known for effectively handling extensive and complex datasets. To achieve the highest modeling accuracy, the parameters of each model were meticulously fine-tuned. Upon evaluation, the results revealed that the GPR models outperformed other techniques in various metrics, including Root Mean Square Error (RMSE), R-squared, Mean Absolute Error
Who reads Creating Rutting Prediction Models through Machine Learning Techniques Utilizing the Long-Term Pavement Performance Database?
It is typically read by researchers, students, and practitioners in Environmental Science.
- Author
- Ali Juma Alnaqbi; Waleed Zeiada; Ghazi G. Al-Khateeb; Khaled Hamad; Samer Barakat
- Publisher
- MDPI AG
- Published
- 2023
- Language
- EN
- Field
- Environmental Science (Social Sciences)