Simulation of time series wind speed at an international airport
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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Simulation
Abstract
The sporadic and unstable nature of wind speed renders it very difficult to predict accurately to serve various decisions,
such as safety in the air traffic flow and reliable power generation system. In this study we assessed the autoregressive
integrated moving average (ARIMA) and artificial neural network (ANN) models on the wind speed time series problem.
Data on wind speed and minimum and maximum temperatures were evaluated. Wind speed was established to follow a
time series that fluctuated around ARIMA (0,1,1) and ARIMA (1,1,1). The optimal ANN model was established at 10 hidden
neurons. The performance indices considered all indicated that the ANN wind speed model was superior to the
ARIMA model. Wind speed prediction accuracy can be improved to secure the safety of air traffic flow as well support
the implementation of a reliable and secure power generation system at the airport
Description
Keywords
Wind speed, autoregressive, integrated moving average
Citation
Wesonga, R., Nabugoomu, F., Ababneh, F., & Owino, A. (2019). Simulation of time series wind speed at an international airport. Simulation, 95(2), 171-184. DOI: 10.1177/0037549718788955