Simulation of time series wind speed at an international airport

Ronald Wesonga*, Fabian Nabugoomu, Faisal Ababneh, Abraham Owino

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

3 اقتباسات (Scopus)

ملخص

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.

اللغة الأصليةEnglish
الصفحات (من إلى)171-184
عدد الصفحات14
دوريةSimulation
مستوى الصوت95
رقم الإصدار2
المعرِّفات الرقمية للأشياء
حالة النشرPublished - فبراير 1 2019

ASJC Scopus subject areas

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