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相关概念视频

Errors in Global Positioning System01:26

Errors in Global Positioning System

46
Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
46
Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

59
GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
59
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

36
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
36
Field Application of Global Positioning System01:28

Field Application of Global Positioning System

48
The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
48

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自行车数据驱动的应用框架:一个荷兰的案例研究,基于机器学习的自行车延迟估计在使用全国稀缺的GPS数据信号交叉路口全国稀缺的GPS数据.

Yufei Yuan1, Kaiyi Wang2, Dorine Duives1

  • 1Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands.

Sensors (Basel, Switzerland)
|December 23, 2023
PubMed
概括
此摘要是机器生成的。

估计十字路口的自行车延误对于运输性能至关重要. 机器学习模型有效地使用稀疏的GPS数据和外部因素来预测这些延迟,为交通管理和政策提供信息.

关键词:
全球定位系统 (GPS) 的循环数据.自行车延误导致的延误数据驱动的自行车应用程序机器学习是机器学习.有信号的交叉点交叉点.

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科学领域:

  • 运输工程 运输工程
  • 数据科学数据科学数据科学
  • 城市规划 城市规划

背景情况:

  • 各国越来越多地采用数据驱动的方法来评估运输系统.
  • 荷兰已经制定了自行车流量计数和GPS数据收集的协议.
  • 准确估计在信号交叉点的自行车延误对于性能评估至关重要.

研究的目的:

  • 开发一个通用框架来分析循环数据.
  • 通过使用机器学习,估计信号交叉点的平均自行车延误.
  • 评估使用稀疏的GPS数据用于延迟估计的可行性.

主要方法:

  • 利用荷兰每年100万次骑自行车的数据集.
  • 应用了各种机器学习模型:随机森林,k-最近邻居,支持向量回归,极端梯度增强和神经网络.
  • 集成稀疏的GPS循环数据与外部信息,如天气和交叉路口的复杂性.

主要成果:

  • 证明了用不完整的GPS数据估计自行车延误的可行性.
  • 机器学习模型通过结合补充数据源成功预测了延迟.
  • 展示了将稀疏的传感器数据与上下文信息相结合的价值.

结论:

  • 数据驱动的方法,特别是机器学习,可以有效地估计自行车延误.
  • 稀少的GPS数据,当与外部信息增强时,是用于运输分析的可行资源.
  • 调查结果支持信息化的交通管理,自行车政策制定和基础设施规划.