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Updated: Jan 15, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

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一个高精度的短期光伏功率预测模型,基于多变量变量模式分解和门循环单元注意力,带有Crested Porcupine优化器增强的矢量加权平均算法

Jinxiang Pian1, Xianliang Chen1

  • 1School of Electrical and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China.

Sensors (Basel, Switzerland)
|October 16, 2025
PubMed
概括

一个新的混合型号提高了光伏 (PV) 短期功率预测的准确性. 这种先进的系统将数据分解与优化的神经网络相结合,增强可再生能源的整合和电网稳定性.

关键词:
预测光伏功率的预测注意力机制注意力机制有门的循环单元.多变量变量模态分解矢量加权平均算法 矢量加权平均算法

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