Sep 7, 2018 · Ensemble decision tree models combine weak learners to produce a powerful model using one of two methods: boosting or bagging. The gradient ...
Sep 3, 2018 · This paper introduces orthogonal decision trees that offer an effective way to construct a redundancy-free, accurate, and meaningful ...
Intersection Traffic Prediction Using Decision Tree Models. Alajali, Walaa; ;; Zhou, Wei; ;; Wen, Sheng; ;; Wang, Yu. Abstract. Publication: Symmetry. Pub Date ...
Sep 1, 2018 · Three popular ensemble decision tree models are used in the batch learning scheme, including Gradient Boosting Regression Trees (GBRT), Random ...
Feb 26, 2015 · Road planners frequently face the challenge to determine which intersection design provides the best traffic flow for a particular traffic ...
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Oct 2, 2020 · To fill this gap, this research develops a two-layer stacking model for intersection short-term traffic flow forecasting by integrating the. K- ...
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In this. 14 study, traffic violation data were used to analyze the influencing factors associated with traffic violations. 15 and to predict the probability of ...
Apr 28, 2025 · Results show that Random Forest and Gradient Boosting Tree models achieve the best accuracy and generalization, effectively capturing complex ...
In this paper, we propose a Decision-Tree enabled approach powered by deep learning for extracting anomalies from traffic cameras while accurately estimating ...