Estimation of monthly pan evaporation using artificial neural networks and support vector machines

被引：31

作者：

Eslamian, S.S. ^{[1
]}

Gohari, S.A. ^{[1
]}

Biabanaki, M. ^{[1
]}

Malekian, R. ^{[1
]}

机构：

[1] Isfahan University of Technology, Isfahan

来源：

Journal of Applied Sciences | 2008年 / 8卷 / 19期

关键词：

Artificial neural networks; Monthly pan evaporation; Support vector machines;

D O I：

10.3923/jas.2008.3497.3502

中图分类号：

学科分类号：

摘要：

The aim of this study is estimation of monthly pan evaporation using artificial neural networks and support vector machines. In the current study, the meteorological variables including air temperature, solar radiation, wind speed, relative humidity and precipitation were considered monthly. The R2 of ANNs and SVMs models were obtained 0.940 and 0.936, respectively; whereas the Mean Square Error values (MSE) were 1265.22 and 40.98, respectively. Both ANNs and SVMs approaches work well for the data set used in this region, but the SVMs technique works better than the ANNs model. © 2008 Asian Network for Scientific Information.

引用

页码：3497 / 3502

页数：5

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