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Comparison of Estimators of Gumbel Distribution for Modelling Wind Speed Data

Author(s): N. Vivekanandan

Journal: Bonfring International Journal of Data Mining
ISSN 2250-107X

Volume: 02;
Issue: 04;
Start page: 11;
Date: 2012;
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Keywords: Anderson-Darling | Gumbel | Kolmogorov-Smirnov | Mean Square Error | Order Statistics | Wind Speed

Estimation of extreme wind speed potential at a region is of importance while designing tall structures such as cooling towers, stacks, transmission line towers, etc. Assessment of wind speed in a region can expediently be carried out by probabilistic modelling of historic wind speed data using an appropriate extreme value distribution. This paper illustrates the use of five parameter estimation methods of Gumbel distribution for modelling Hourly Maximum Wind Speed (HMWS) data recorded at Delhi and Visakhapatnam regions. Goodness-of-Fit (GoF) tests involving Anderson-Darling and Kolmogorov-Smirnov are used for checking the adequacy of fitting of the method to the recorded data. Root Mean Square Error (RMSE) is used for selection of a suitable method for determination of estimators of Gumbel distribution for modelling HMWS data. The results of GoF tests and RMSE shows that order statistics approach is better suited for estimation of design wind speed for the regions under study.
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