A Co-LNP Academic Award Prediction Mechanism based on the CEw-LSTM Model

The prediction of academic award winners is a challenging task because of the complexities of establishing the appropriate evaluation system and the difficulties in modeling. Although some scholars have studied the prediction of some award winners, the related research on the prediction mechanism of academic awards in the computer field using the academic network and neural network model is still lacking. Therefore, we propose the Co-LNP mechanism, which is an academic award prediction mechanism based on a scholar cooperation network towards NSFDYS. We design a prediction model named CEw-LSTM model and provide the "improved LSTM model + artificial rule" prediction strategy to improve the prediction performance and effectiveness. Empirical studies demonstrate that the Co-LNP academic award prediction mechanism proposed in this paper has a good effect and practical application value in the computer field.