相关实验视频
Updated: Jun 8, 2025

09:39
Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
Published on: November 18, 2019
5.8K
在基于无人机的城市交通监控系统中,用于交通流量预测的时空空间卷积图神经网络
Wenming Ma1, Zihao Chu2, Hao Chen2
1School of Computer and Control Engineering, Yantai University, Yantai, 264005, China. mwm@ytu.edu.cn.
Scientific reports
|November 5, 2024
概括
本研究引入了用于交通预测的进化图形神经网络,通过动态更新交通数据关系来提高准确性. 这种新的方法改进了现有的模型,以便更可靠地预测交通流量.
科学领域:
- 人工智能的人工智能
- 运输系统 运输系统
- 数据科学数据科学数据科学
背景情况:
- 无人驾驶飞行器 (UAV) 越来越多地用于交通管理.
- 图形神经网络 (GNN) 可以处理时空流量数据,但会受到过度平滑的影响.
- 现有的空间时间图常规微分方程 (STGODE) 模型由于固定的邻近矩阵而缺乏适应动态交通信息的能力.
研究的目的:
- 开发一种自适应图形神经网络模型,以改善流量预测.
- 在当前的交通预测模型中解决静态语义邻近矩阵的局限性.
- 通过使用动态数据关系来增强复杂和可变的流量模式的捕获.
主要方法:
- 提出了用于交通预测的进化图形神经网络 (EGNN).
- 在GNN框架内实施了一个不断更新的语义邻矩阵.
- 利用神经常规微分方程 (NODE) 来构建更深层次的 GNN 架构.
主要成果:
- 拟议的EGNN模型与最先进的基准相比,表现优越.
- 语义邻矩阵的动态演变有效地捕获了实时流量特征和关系.
- 该模型显示了处理交通模式的复杂性和变异性的增强能力.
结论:
- 进化图神经网络在交通预测准确度方面取得了重大进展.
- 图形结构的动态适应对于模拟复杂的,现实世界的交通动态至关重要.
- 这种方法为基于无人机的交通监控系统提供了更强大,更可靠的解决方案.
相关概念视频
Uniform Depth Channel Flow: Problem Solving
58
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
58
Uniform Depth Channel Flow
63
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
63
Rapidly Varying Flow
53
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
53
Turbulent Flow: Problem Solving
96
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
96
Turbulent Flow
146
Turbulent flow is characterized by unpredictable fluctuations in velocity and pressure, which result in a chaotic fluid movement distinct from the orderly patterns of laminar flow. While laminar flow is governed by smooth, parallel layers with minimal mixing, turbulent flow exhibits highly irregular, three-dimensional patterns. This behavior arises due to instabilities in the fluid's velocity profile, and amplifies as the flow velocity increases. Minor disturbances, known as turbulent...
146
Plane Potential Flows
369
Plane potential flows simplify fluid motion by assuming the fluid to be irrotational and incompressible. These characteristics allow these flows to be described by a velocity potential function, ϕ, representing the flow speed in a given direction, and a stream function, ψ, that visualizes the flow path, both governed by Laplace's equation. These parameters help in estimating flow patterns, velocity distributions, and pressure fields around various hydraulic structures.
Uniform...
Uniform...
369

