… not necessarily enough to accurately predict the resource future status and behavior, which
is … a more accurate ensemble prediction algorithm that combines the prediction values of its …

… ensemble prediction model is proposed. The approach includes LRIME algorithm, as well
as the learners that constitute the stacking ensemble learning… consumption behavior varies, …

… 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 …

… In this study, a stacking ensemble machine learning model was employed against … Results
revealed that the ensemble model provides higher accuracy with 98.90% as part of training …

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

… 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 …

… application behavior in a long period while the second category stores the new behavior of
applications which correspond to online learning. The run-length encoding based prediction …

… ) 10-fold cross-validation and (ii) predicting the SI behavior of a set of unseen data excluded
… performance of deep and ensemble learning techniques for prediction of SI with the test …

… The response unit alerts the system’s administrator with abnormal behavior based on the
predicted attack profile. The response unit also updates the new signature of the attack types …

… and behaviours of students’ factors using ensemble learning contributes to … learning
techniques to identify students' performance. This study examined different ensemble prediction …