Precipitation Interception Modelling Using Machine Learning Methods - The Dragonja River Basin Case Study

被引：0

作者：

Stravs, L. ^{[1
]}

Brilly, M. ^{[1
]}

Sraj, M. ^{[1
]}

机构：

[1] Univ Ljubljana, Fac Civil & Geodet Engn, SI-1000 Ljubljana, Slovenia

来源：

PRACTICAL HYDROINFORMATICS: COMPUTATIONAL INTELLIGENCE AND TECHNOLOGICAL DEVELOPMENTS IN WATER APPLICATIONS | 2008年 / 68卷

关键词：

Precipitation interception; forest hydrological cycle; the Dragonja River basin; machine learning; decision trees; M5; method; J4.8;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The machine learning methods M5 for generating regression and model tree models and J4.8 for generating classification tree models were selected as the methods for analysis of the results of experimental measurements in the Dragonja River basin. Many interesting and useful details about the process of precipitation interception by the forest in the Dragonja River basin were found. The resulting classification and regression tree models clearly show the degree of influence and interactions between different climatic factors, which importantly influence the process of precipitation interception.

引用

页码：347 / 358

页数：12

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