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Updated: Jun 25, 2025

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将PSO和SVR同化为一个改进的ARIMA模型,用于每月降水预测

Laleh Parviz1, Mansour Ghorbanpour2

  • 1Faculty of Agriculture, Azarbaijan Shahid Madani University, Tabriz, Iran. laleh_parviz@yahoo.com.

Scientific reports
|May 27, 2024
PubMed
概括

使用改进的ARIMA (IARIMA) 模型实现了准确的每月降水预报. 在降水预测方面,IARIMA-C粒子群集优化 (PSO) 方法表现出优于IARIMA-支持向量回归 (SVR) 的性能.

关键词:
这就是IARIMA-C-PSO.改进了ARIMA的功能每个月一次,每月一次.在RPD中使用RPD.这是一个SVRSVR.

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Precipitation and Co-precipitation

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Precipitation Gravimetry

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Change in atmospheric pressure with height is particularly interesting. The decrease in atmospheric pressure with increasing altitude is due to the decreasing gravitational force per unit area as we move away from the surface of the earth.
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