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相关概念视频

Time-Series Graph00:54

Time-Series Graph

4.3K
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...
4.3K
Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

91
Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
91
Prediction Intervals01:03

Prediction Intervals

2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
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Electrostatic Boundary Conditions01:16

Electrostatic Boundary Conditions

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Consider an external electric field propagating through a homogeneous medium. When the electric field crosses the surface boundary of the medium, it undergoes a discontinuity. The electric field can be resolved into normal and tangential components. The amount by which the field changes at any boundary is given by the difference between the field components above and below the surface boundary.
The surface integral of an electric field is given by Gauss's law in integral form and is related to...
463
Boundary Conditions for Current Density01:25

Boundary Conditions for Current Density

858
Current density becomes discontinuous across an interface of materials with different electrical conductivities. The normal component of the current density is continuous across the boundary.
858
Areas Within Irregular Boundaries01:26

Areas Within Irregular Boundaries

74
Calculating areas within irregular boundaries, such as along rivers or curved roads, is crucial in various fields, including surveying, engineering, and environmental management. Surveyors often begin by creating a traverse, a connected series of straight lines approximating the area's boundary. The coordinates of each traverse point are essential for calculating the enclosed area. The double meridian distance formula is a widely used technique for this purpose. This method utilizes the...
74

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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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单边边界时间序列预测.

Chao-Min Chang1, Cheng-Te Li2, Shou-De Lin1

  • 1Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.

Frontiers in big data
|June 21, 2024
PubMed
概括

这项研究引入了一种新的方法,用于使用单边边界条件进行时间序列预测. 新方法使用单边平均平方误差 (UMSE) 和双模型结构,以提高偏斜数据集的准确性.

科学领域:

  • 数据科学数据科学数据科学
  • 机器学习 机器学习

背景情况:

  • 传统的时间序列预测模型与单边边界条件作斗争,导致系统的高估或低估.
  • 现有的方法缺乏专门的框架来有效处理偏斜的数据集.

研究的目的:

  • 在单边边界条件下开发一个用于准确时间序列预测的新框架.
  • 为了解决偏差数据集中的低估偏差,并提高预测精度.

主要方法:

  • 引入单边平均平方误差 (UMSE),一个不对称的损失函数.
  • 实施双模结构,单独处理低估和准确估计的数据.
  • 利用特征重建来重新捕获隐藏的数据动态.

主要成果:

  • 在各种数据集中使用LightGBM和GRU模型证明了拟议方法的卓越准确性和稳定性.
  • 验证了UMSE和双模结构在处理低估偏差方面的有效性.
  • 与传统模型和现有方法相比,展示了显著的改进.

结论:

  • 这种新的方法为偏斜的数据集提供了准确而强大的时间序列预测.
  • 该方法与模型无关,在各种行业中广泛适用.
关键词:
不对称的损失函数的功能.双重模型结构结构是双重模型结构.功能重建重建的重建.时间序列预测时间序列预测一个单边的边界.

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  • 这项研究为关键预测应用中先进的分析模型铺平了道路.