期刊名称：Bonfring International Journal of Data Mining
印刷版ISSN：2250-107X
电子版ISSN：2277-5048
出版年度：2012
卷号：2
期号：4
页码：11-15
DOI：10.9756/BIJDM.10079
语种：English
出版社：Bonfring
摘要：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.
关键词：Anderson-Darling; Gumbel; Kolmogorov-Smirnov; Mean Square Error; Order Statistics; Wind Speed
