… -model-based clustering to achieve the reliable spatiotemporal differentiation identification
of dam behavior and a multioutput ensemble learning framework coupled with the extreme …

… a new approach based on ensemble learning methods to improve their … behavioral anomalies
as a case study, we show the interest of this approach for its improvement of the prediction …

… In order to provide a feasible solution, this paper presents a framework for predicting the …
before due to the unguided overfitting behavior of the ensemble model in the training stage. The …

… ensemble neural network (PENN) is proposed to predict the long-term dynamic behavior.
The … Based on the above, learning-based models have been proposed as alternatives for the …

… an academic prediction model based on feature engineering and ensemble learning. Firstly,
… It shows that students' learning behavior in class has a great impact on course performance. …

… -IoT, a deep ensemble learning framework for IoT anomaly detection and prediction using
SDN, … It uses the SVM algorithm at the SDN controller to monitor and learn the behavior of IoT …

… prediction accuracy, we proposed an intelligent learning system … Experimental findings reveal
that the suggested learning … Furthermore, it was also observed that the proposed learning …

… To further improve the intention prediction accuracy, an ensemble RNN structure is
developed. Next, it is essential to understand the naturalistic driver behaviors and analyze the …

… ’ self-query behaviors on the Internet with the epidemic spreading process. An epidemic
spreading prediction method that combines EMD with ensemble learning techniques is …

… A hybrid model blending SVM and DNN ensemble predictions is developed to quantify
the … Events: This attribute provides the basic characteristics of anomalous behavior and its …