.

概括

本研究介绍了一种使用神经微分方程进行更准确的金融波动性预测的持续波动性预测模型 (CVFM). 在预测准确性和识别高波动性方面,CVFM的表现优于现有模型.

相关概念视频

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
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Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

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The Swing Equation01:21

The Swing Equation

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Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

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Line Section Model
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Classification of Systems-II01:31

Classification of Systems-II

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Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
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