Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/13628
Title: Robust regression technique to estimate the global radiation
Authors: Sivamadhavi, V
Selvaraj, R Samuel
Keywords: Global Solar Radiation
Linear Least Squares
Robust Regression
Robust Least Square (RLS)
Sunshine Duration
Issue Date: Feb-2012
Publisher: NISCAIR-CSIR, India
Abstract: In the present paper, the monthly mean daily global radiation on a horizontal surface has been correlated with meteorological parameters. Sunshine duration was proved to be the best predictor. Overall and month-wise regression equations have been developed using sunshine duration to estimate monthly mean daily global radiation on a horizontal surface at Chennai, India. For this, data analysis was done for a period of twenty years from 1990 to 2009. Overall regression coefficients for linear, quadratic and cubic polynomials were determined using linear least squares and robust regression methods. Robust method yielded a better set of values for the regression constants. The second order polynomial equation has been found to be an optimum fit for global radiation. Month-wise second order regression equations have been developed using robust method. An excellent agreement has been found between the values estimated from the proposed model and the measured values.
Description: 17-25
URI: http://hdl.handle.net/123456789/13628
ISSN: 0975-105X (Online); 0367-8393 (Print)
Appears in Collections:IJRSP Vol.41(1) [February 2012]

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