2022. “Flowfield Prediction of Airfoil Off-Design Conditions Based on a Modified Variational Autoencoder.” AIAA Journal 60 (10): 5805–20. https://doi.org/10.2514/1.J061972. wing flow field prediction Yang, Yunjia, Runze Li, Yufei Zhang, Lu Lu, and Haixin Chen*. 2024. “...
Given a design geometry space and a range of flow condition of interest, if we have enough data, it would be easy to predict flow field of an airfoil under a particular flow condition by building a prediction model as the method does in Ref. 10. However, collecting large-scale flow field...
Code Issues Pull requests General flow field prediction for data-based optimization pytorch flowfield ai4science Updated Mar 15, 2025 Python vharivinay / Flow-field-using-noise Star 9 Code Issues Pull requests Animating flow filed like structures using P5JS flow generative-art p5js perlin...
Flow field prediction using deep learning is a promising method to provide a rich source of information for isolator operating state detection. A data-driven model is proposed for the prediction of the flow field in an isolator by fusion convolutional neural networks using measurements of the ...
At the same time, new arriving data are processed in real-time, and a more effective prediction system is explored in the field of dynamic training40, to further optimize the design of the traffic flow prediction model and improve its generalization ability....
""" Upsample flow field [H/8, W/8, 2] -> [H, W, 2] using convex combination """ N, _, H, W = flow.shape mask = mask.view(N, 1, 9, 8, 8, H, W) mask = torch.softmax(mask, dim=2) up_flow = F.unfold(8 * flow, [3,3], padding=1) ...
Modifier and TypeField and Description static final FlowLogFormatType JSON Static value JSON for FlowLogFormatType. Constructor Summary 展開資料表 ConstructorDescription FlowLogFormatType() Deprecated Use the fromString(String name) factory method. Creates a new instance of FlowLogFormatType va...
Intriguingly, what could be interpreted as a formal definition of means-ends fusion appears in the field of artificial intelligence. It has proven useful to have artificial agents aim to maximize a quantity called empowerment: the maximum of the mutual information between the agent’s actions and ...
Traffic forecasting is a fundamental and challenging task in the field of intelligent transportation. Accurate forecasting not only depends on the historical traffic flow information but also needs to consider the influence of a variety of external factors, such as weather conditions and surrounding POI...
Due to the stochastic and nonlinear nature of traffic flow, researchers have paid much attention to nonparametric methods in the traffic-flow forecasting field. Davis and Nihan used the k-NN method for short-term freeway traffic forecasting and argued that the k-NN method performed comparably with...