Daily rainfall forecasting using an ensemble technique based on singular spectrum analysis

被引：0

作者：

Masulli, F ^{[1
]}

Baratta, D ^{[1
]}

Cicioni, G ^{[1
]}

Studer, L ^{[1
]}

机构：

[1] Univ Genoa, Ist Nazl Fis Mat, DISI, I-16146 Genoa, Italy

来源：

IJCNN'01: INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS | 2001年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In previous work, we have proposed a constructive methodology for temporal data learning supported by results and prescriptions related to the Takens-Mane theorem and using the Singular Spectrum Analysis in order to reduce the effects of the possible discontinuity of the signal. In this paper we present some new results concerning the application of this approach to the forecasting of the individual rainfall intensities series collected by 135 stations distributed in the Tiber basin.

引用

页码：263 / 268

页数：6

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