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相关概念视频

Prediction Intervals01:03

Prediction Intervals

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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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End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

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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.
For potentiometric titration, the Gran plot is created by plotting...
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Time-Series Graph00:54

Time-Series Graph

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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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Series R—L Circuit Transients01:22

Series R—L Circuit Transients

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In a series resistor-inductor (R-L) circuit, closing the switch at the start of the time period simulates a three-phase short circuit, a fault condition where all three phases of an unloaded synchronous machine are short-circuited. When there is no fault impedance and no initial current, the initial voltage is determined by the phase angle of the source voltage.
Using Kirchhoff's Voltage Law (KVL) to analyze this circuit helps determine the total asymmetrical fault current, which consists...
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Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

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In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
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Basic Continuous Time Signals01:22

Basic Continuous Time Signals

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Basic continuous-time signals include the unit step function, unit impulse function, and unit ramp function, collectively referred to as singularity functions. Singularity functions are characterized by discontinuities or discontinuous derivatives.
The unit step function, denoted u(t), is zero for negative time values and one for positive time values, exhibiting a discontinuity at t=0. This function often represents abrupt changes, such as the step voltage introduced when turning a car's...
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基于连接器的短时间序列预测.

Wenjuan Gao1,2, Cirong Li1, Siyu Dong3

  • 1School of Business and Management, Jilin University, No. 2699 Str. Qianjin, Changchun, 130012, Prov. Jilin, China.

Scientific reports
|February 27, 2025
PubMed
概括

这项研究引入了新的连接器来合并短时间序列,以改善预测模型. 这些方法,包括线性插值和随机振动,增强了综合数据的经验模式分解 (EMD) 分析.

关键词:
连接器 连接器 连接器经验模式分解分解短时间序列预测

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科学领域:

  • 时间序列分析时间序列分析.
  • 信号处理 信号处理
  • 机器学习是机器学习.

背景情况:

  • 经典预测模型由于不完整的模式信息而难以处理短时间序列.
  • 短序列的直接连接可以引入显著的偏差并破坏数据规律性.

研究的目的:

  • 提出一个有效结合短时间序列的多序列预测模型.
  • 通过解决直接连接的局限性来提高预测模型的性能.

主要方法:

  • 数据集的规范化.数据集的规范化.
  • 引入了两种连接器类型:线性互插和随机振动 (LRV) 的线性互插.
  • 实证模式分解 (EMD) 对连接序列的应用.

主要成果:

  • 拟议的连接器有助于EMD分解更好地反映原始短系列特征的子序列.
  • LRV连接器对于定期的多系列数据是有效的.
  • 线性插值连接器适用于非周期短序列.

结论:

  • 开发的多序列预测模型,利用连接器和EMD,为处理短时间序列数据提供了优越的方法.
  • 连接器的选择取决于时间序列的周期性,在应用中提供灵活性.