Experimental results demonstrate that ensemble regression models outperform conventional regression techniques in terms of prediction accuracy and robustness, and indicate that XGBoost provides the best overall performance while maintaining computational efficiency.
The tuned RF emerged as the most reliable and robust classifier, offering high predictive accuracy with reduced overfitting risk, and hyperparameter tuning proved particularly beneficial for SVM and KNN, substantially improving their generalization capabilities, while producing minimal changes in already well-optimized...
Gulala Ali Hama Amin, S. Hassan, Rebwar Khalid Muhammed et al.· Academic Journal of Internat...· 0 citations
Accurate traffic volume prediction is essential for effective traffic management and transport planning, particularly on major freeway corridors. This study examines hourly traffic volume prediction using the Metro Interstate Traffic Volume Dataset by applying classical machine learning models together with systematic...
S. Nissanka, Damayanthi Herath, Panduka Neluwala et al.· Moratuwa Engineering Researc...· 0 citations
A novel approach to optimizing intelligent transportation models using the hybrid Foraging Habitat Selection Particle Swarm Optimization–Random Forest (FHSPSO-RF) technique, which can adaptively optimize several parameters of the Random Forest classifier, namely the number of trees, maximum depth, and minimal samples p...
Jing-Yi Zhang· ITM Web of Conferences· 0 citations
The findings show the prospective of machine learning techniques, particularly the Random Forest model, which delivers the highest accuracy in predicting hybrid vehicle energy consumption, which supports more informed decision-making for developing eco-friendly transport solutions, reducing fuel consumption and emissio...
Bishawajit Chakraborty, Arpita Paul, Bhubon Thiotonius Costa et al.· Engineering· 0 citations
The study found a positive relationship between traffic volume and temperature, while traffic volume decreased significantly on weekends, and the models with the highest prediction accuracy were XGBoost, Artificial Neural Network, and Ridge Regression.
Vildan Gülpınar Demirci, Busra Ozdenizci Kose, F. Huseynov et al.· Hitit Sosyal Bilimler Dergis...· 0 citations
The custom score which is sum of MAE, RMSE, MAPE and time processing values is calculated and the best model obtained is the custom stacked regression model has custom score of 111.41 which is very less as compared to other regression models.
Priyanka Goyal, U. Patel· International Journal of Edu...· 0 citations
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