Estimation of dew point temperature using SVM and ELM for humid and semi-arid regions of India

被引：11

作者：

Deka P.C. ^{[1
]}

Patil A.P. ^{[2
]}

Yeswanth Kumar P. ^{[1
]}

Naganna S.R. ^{[1
]}

机构：

[1] Department of Applied Mechanics and Hydraulics, National Institute of Technology Karnataka, Surathkal

[2] Department of Civil Engineering, Dr. Daulatrao Aher College of Engineering, Karad

来源：

ISH Journal of Hydraulic Engineering | 2018年 / 24卷 / 02期

关键词：

Dew point temperature; ELM; humid region; semi-arid region; SVM;

D O I：

10.1080/09715010.2017.1408037

中图分类号：

学科分类号：

摘要：

The dew point temperature is the temperature at which the moisture in the air begins to condense into dew or water droplets. The accurate estimation of the dew point temperature is very important as it controls the heat stress on humans, detects fluctuations of evaporation rates, and humidity trends. The dew point temperature is a significant parameter particularly required in various hydrological, climatological and agronomical related researches. This study proposes Support Vector Machine (SVM) and Extreme Learning Machine (ELM) models for the estimation of daily dew point temperature. The daily measured weather data (Wet bulb temperature, relative humidity, vapor pressure and dew point temperature) of humid and semi-arid regions of India were used for model development. The statistical indices, namely Mean Absolute Error, Root Mean Square Error, and Nash Sutcliffe Efficiency were adopted to evaluate the performances of these two models. The merit of the ELM model is evaluated against SVM technique in the estimation of dew point temperature. The proposed ELM models demonstrated much greater capability than the SVM models in the estimation of daily dew point temperature. © 2017 Indian Society for Hydraulics.

引用

页码：190 / 197

页数：7

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