GRAPH neural networksACADEMIC achievementGRAPH algorithmsONLINE educationAcademic performance is a crucial issue in the field of Online learning analytics. While deep learning-based models have made significant progress in the era of big data, many of these methods need help to capture the complex ...
Implementing and Training a Neural Network with PyTorch 965 -- 22:57 App 使用PyTorch玩转音频和音乐系列 - 5. Extracting Mel Spectrograms with Pytorch and Torchaudio 867 -- 23:00 App 使用PyTorch玩转音频和音乐系列 - 4. Custom Audio PyTorch Dataset with Torchaudio 604 -- 16:00 App 使用PyTorch...
Two different three-layer-based perceptron neural networks were devised to predict the 5′ and 3′ splice sites. In case of 5′ site determination, a network with 3 neurons at the hidden layer was chosen, while in case of 3′ site 20 neurons acted more efficiently. Both neural nets were...
The fully connected neural networks and the long-short-term memory networks were employed to establish the neural networks for motion predictions. The effects of network architectures and time steps were investigated in depth. The predicted results were compared with the measurements and the predictions...
We use the load scenarios to estimate the uncertainty in the NN load forecast This compares favourably with estimates based solely on historical load forecast errors. 展开 关键词: neural networks weather ensemble predictions Load forecasting DOI: 10.1109/MPER.2002.4312413 被引量: 667 ...
The comparison of simulated results with observed data indicates that neural network is able to learn the driver behavior more realistically than other standard modeling and is able to perform short term prediction with sufficient accuracy. 展开 关键词: Traffic Simulation Lane Change Process Neural ...
p pBackground/p pProtein-Carbohydrate interactions are crucial in many biological processes with implications to drug targeting and gene expression. Nature... A Malik,S Ahmad - 《Bmc Structural Biology》 被引量: 174发表: 2007年 Neural network‐based prediction of mutation‐induced protein stability...
系统标签: signalpsignalneuralspasedeeppredictions BriefCommuniCation https://doi/10.1038/s41587-019-0036-z 1 DepartmentofBioandHealthInformatics,TechnicalUniversityofDenmark,KgsLyngby,Denmark. 2 DepartmentofBiochemistryandBiophysics, StockholmUniversity,Stockholm,Sweden. 3 ScienceforLifeLaboratory,StockholmUniversity...
& Shen, Y. Deepaffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks. Bioinformatics 35, 3329–3338 (2019). Article Google Scholar Tsubaki, M., Tomii, K. & Sese, J. Compound–protein interaction prediction with end-to-end ...
But no one uses BP neural network to study residual interactions. In this paper, we obtained a description and prediction model for residual interactions based on BP neural network. By combining experimental values with residual interactions model, we successfully calculate the nuclear masses of A ...