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相关概念视频

End Point Prediction: Gran Plot01:07

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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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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...
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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...
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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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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...
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相关实验视频

Updated: Jul 19, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study
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ADSTGCN:一个动态自适应的深度时空图形卷积网络,用于多步骤的交通预测.

Zhengyan Cui1, Junjun Zhang1, Giseop Noh2

  • 1Department of Computer Information Engineering, Cheongju University, Cheongju 28503, Republic of Korea.

Sensors (Basel, Switzerland)
|August 12, 2023
PubMed
概括

本研究介绍了动态自适应深度时空图卷积网络 (ADSTGCN),以改善多步骤的流量预测. 该模型克服了过度平滑,并提高了适应动态交通条件的灵活性.

关键词:
适应式图形的构建.深度图形卷积网络的卷积网络.时空图的时间空间图.交通预测 交通预测

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科学领域:

  • 人工智能的人工智能
  • 运输工程 运输工程
  • 数据科学数据科学数据科学

背景情况:

  • 多步骤的交通预测是复杂的,因为动态的交通条件.
  • 图形卷积网络 (GCNs) 提取空间流量数据,但通常遭受浅层架构和过度平滑的影响.
  • 由于固定的节点结构,现有的模型缺乏灵活性.

研究的目的:

  • 开发一种新的流量预测模型,解决现有的GCNs的局限性.
  • 为了减轻用于交通预测的更深的GCN中的过度平滑现象.
  • 增强用于现实世界网络的流量预测模型的适应性和灵活性.

主要方法:

  • 拟议的动态自适应深度时空图卷积网络 (ADSTGCN).
  • 实现了动态隐藏层连接和适应性重量调整,以打击过度光滑.
  • 引入了一个参数共享适应矩阵,用于学习空间依赖性和网络结构适应.

主要成果:

  • 在更深层的GCN中,ADSTGCN有效地解决了过度平滑的问题.
  • 该模型在多步骤的交通预测中表现得更好.
  • 对高速公路和城市道路网络的评估显示出有希望的结果.

结论:

  • ADSTGCN提供了一种更强大,更灵活的交通预测方法.
  • 适应机制增强了模型捕捉动态交通模式的能力.
  • 拟议的方法显示了现实世界交通预测应用的巨大潜力.