… has a different impact on student performance. Therefore, this paper proposes a novel …
performance prediction by making full use of both student behavior features and exercise features …

… a traffic prediction model using the multi-stream feature fusion … performance of the proposed
model, we perform experiments for the traffic flow prediction and the traffic speed prediction …

… features, we propose a novel feature fusion LSTM-BPNN model. LSTM-BPNN first learns the
cross-sectional and time-series features … model, named LSTM-BPNN, for the IRI prediction …

… feature–level to compare their performance. The best combination of fusion and prediction
… a great impact on the performance of the prediction model which are explored in this study. …

… For instance, Rostami [35] improved the well-known Colorado School of Mines (CSM)
model for TBM's performance prediction based on various laboratory tests. Gong and Zhao [17] …

… Therefore, a novel feature fusion based ensemble method is proposed in this paper to
integrate the above features and improve the RUL prediction performance. As illustrated in Fig. 1, …

… to enhance the performance of heart disease … prediction using ensemble deep learning
and feature fusion approaches. First, the feature fusion method combines the extracted features …

… 3.5 Prediction Network The user fusion stack and item fusion stack will be put into the prediction
network after the cross feature fusion … size influences the fusion performance, but not K. …

… -stage feature aggregation is beneficial to improving the performance of Transformer in dense
prediction … to emphasise local features and integrate them into global features, making the …

… as the features that markedly affect the linkprediction performance. 2) We built a novel link-prediction
model … feature fusion process and learns a function to hierarchically aggregate the …