A Data Mining Application of Local Weather Forecast for Kayseri Erkilet Airport

Year 2019, , 103 - 113, 01.03.2019

Eda Çınaroğlu , Osman Unutulmaz

https://doi.org/10.2339/politeknik.391801

Abstract

Data mining is a process used for the discovery of
data correlation; the technique includes successful applications in the mass
data field. Aeronautic meteorology is one of them. It includes the observation
and forecast of meteorological events and parameters such as turbulence, rain,
frost, fog, thunderstorm, etc. that affect flight operations. Aeronautic
meteorology studies in the field of aviation. Understanding meteorological
events is not possible without the observation of many parameters which are
related to each other. Previous mass data should be overviewed for the future
forecast. Expert opinions are also necessary in the process of analysis. At
this point, data mining makes a great contribution to the analysis of mass
data. This study aims at revealing the correlation between meteorological
parameters that affect aviation and finding rules by classification. Forecasts
were improved with relational analysis. As a result, reliable rules were
identified that include estimation of fog, rain, snow, hail and thunderstorm
events for Kayseri Erkilet Airport and these rules were analyzed in terms of
their accuracy and reliability.

Keywords

Data mining, aeronautical meteorology, classification, finding rules

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