65 research outputs found
Wind Speed Forecasting with Missing Values
No full text7th International Conference on Information Science and Technology (ICIST) -- APR 16-19, 2017 -- Da Nang, VIETNAMWOS: 000403402600010In this study, a new short term wind speed forecasting approach, which uses long term past observations, is proposed. The performance assessment of the wind speed forecasting framework is carried out using real data from meteorological stations in Marmara region of Turkey. The data sets are not complete due to equipment failures. The proposed approach builds on data de-trending, covariance-factorization via a subspace method, and one-step-ahead and multi-step-ahead Kalman filter prediction ideas. It is shown that trimming of diurnal, weekly, monthly, and annual patterns in data significantly enhances estimation accuracy. Experimental test results demonstrate that the proposed multi-step-ahead forecasting outperforms the benchmark values computed with the persistent forecasting models.City Univ Hong Kong, Vietnam Korea Friendship Informat Technol Coll, Hong Kong Web Soc, IEEE Syst, Man & Cybernet SocAnadolu University Scientific Research Projects Fund [1602F070]The first author was supported by the Anadolu University Scientific Research Projects Fund under Grant 1602F070
A New Hybrid Approach for Wind Speed Prediction Using Fast Block Least Mean Square Algorithm and Artificial Neural Network
No full textWOS: 000387376100001A new hybrid wind speed prediction approach, which uses fast block least mean square (FBLMS) algorithm and artificial neural network (ANN) method, is proposed. FBLMS is an adaptive algorithm which has reduced complexity with a very fast convergence rate. A hybrid approach is proposed which uses two powerful methods: FBLMS and ANN method. In order to show the efficiency and accuracy of the proposed approach, seven-year real hourly collected wind speed data sets belonging to Turkish State Meteorological Service of Bozcaada and Eskisehir regions are used. Two different ANN structures are used to compare with this approach. The first six-year data is handled as a train set; the remaining one-year hourly data is handled as test data. Mean absolute error (MAE) and root mean square error (RMSE) are used for performance evaluations. It is shown for various cases that the performance of the new hybrid approach gives better results than the different conventional ANN structure.Anadolu University Scientific Research Projects Fund [1505F512]This work was supported by Anadolu University Scientific Research Projects Fund with Project no. 1505F512. The received fund covers the costs to publish in open access. And the author is grateful to the Turkish State Meteorological Service for providing the data
Short-term wind speed forecasting by spectral analysis from long-term observations with missing values
No full textWOS: 000395963500050In this paper, we propose a novel wind speed forecasting framework. The performance of the proposed framework is assessed on the wind speed measurements collected from the five meteorological stations in the Marmara region of Turkey. The experimental results show that trimming of the diurnal, the weekly, the monthly, and the annual patterns in the measurements significantly enhances the estimation accuracy. The proposed framework builds on data de-trending, covariance-factorization via a recently developed subspace method, and one-step-ahead and/or multi-step-ahead Kalman filter prediction ideas. The data sets do not have to be complete. In fact, as in sensor failures, intermittently or sequentially missing measurements are permitted. The numerical experiments on the real data sets show that the wind speed forecasts, in particular the multi-step-ahead forecasts, outperform the benchmark values computed with the persistence forecasting models by a clear differenceAnadolu University [1602F070]The work of the first author was supported by the Anadolu University Scientific Research Projects Fund under Grant 1602F070
Recombinant Factor VIIa for Severe Gastrointestinal Hemorrhage Associated with Crohn Disease
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GI MOTILITY TESTING: A LABORATORY AND OFFICE HANDBOOK BY HENRY P. PARKMAN, RICHARD W. CALLUM, AND SATISH S.C. RAO
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