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MODELUNG OF PAN EVAPORATION USING SUPPORT VECTOR MACHINES ALGORITHM

ABSTRACT This paper present results of pan evaporation estimations using Support Vector Machines (SVMs) based approach for the meteorological data from Manasgaon climatic station near Anand Sagar Reservoir, Shegaon. At this station four meteorological variables are measured simultaneously, namely, air temperature, wind speed, sunshine hours and relative humidity. The SVMs architecture involves in using one output parameter (i.e. evaporation) and up to four input parameters representing air temperature, wind speed, sunshine hours and relative humidity. The performance of SVMs approach was compared with multiple linear regression using different combination of meteorological parameters so as to judge the significance of the input parameters in estimating the evaporation. The SVMs algorithm provide good estimation of evaporation with high correlation coefficient along with low Root Mean Square Error. Further, the Scatter Plot between the actual and estimated values of evaporation suggests that most of the values lie within a scatter of ±15%. The findings of this study suggest the usefulness of SVMs algorithm technique in estimating the pan evaporation from reservoirs.