Confidence Interval Approach to Weather Forecasting with Horizon Based Genetic Programming

Year 2024, , 451 - 462, 26.01.2024

Ömer Mintemur

https://doi.org/10.29130/dubited.1188691

Abstract

Being able to forecast events has always been important for humans. Humans did forecasting by inspecting movements of material and non-material objects in ancient times. However, thanks to the technological developments and the increasing amount of data in recent years, forecasting is now done by computers, especially by machine learning methods. One of the areas where these methods are used frequently is numerical weather forecasting. In this type of forecast, short, medium and long-term weather forecasts are made using historical data. However, predictions are inherently error-prone phenomena and should be stated which error range the predictions fall. In this study, numerical weather forecasting was done by combining Genetic Programming and Inductive Conformal Prediction method. The effect of 10 and 20 days of historical data on short (1-day), medium (3-days) and long-term (5-days) weather forecasts was examined. Results suggested that Genetic Programming has a good potential to be used in this area. However, when Genetic Programming was combined with the Inductive Conformal Prediction method, it was shown that forecasts gave meaningful results only in short-term; forecasts made for medium and long-term did not produce meaningful results.

Keywords

Artificial Intelligence, Confidence Interval, Prediction, Genetic Programming

Ufuk Amaçlı Genetik Programlama ile Hava Durumu Tahminine Güven Aralıklı Yaklaşım

Abstract

Olayları önceden tahmin edebilmek insanlar için her zaman önemli olmuştur. Eski zamanlarda insanlar tahminlerini maddesel ve maddesel olmayan cisimlerin hareketlerine göre yapmışlardır. Ancak, son yıllardaki teknolojik gelişmeler ve veri miktarındaki artış sayesinde tahmin çalışmaları bilgisayarlar tarafından, özellikle de makine öğrenmesi metotları tarafından yapılmaktadır. Bu metotların kullanıldığı en önemli alanlardan bir tanesi de sayısal hava durumu tahminidir. Bu tahmin çeşidinde, tarihsel veriler kullanılarak kısa, orta ve uzun vadeli tahminler yapılmaktadır. Ancak, tahminler doğası gereği hataya açık olaylardır ve ortaya çıkan hatanın hangi aralıkta olduğu belirtilmelidir. Bu çalışmada sayısal hava durumu tahmini Genetik Programlama ve Tümevarımsal Güven Aralığı metodu birleştirilerek yapılmıştır. 10 ve 20 günlük tarihsel verinin kısa (1 gün), orta (3 gün) ve uzun (5 gün) vadede yapılan tahminlere olan etkisi incelenmiştir. Sonuçlar Genetik Programlamanın bu alanda kullanılabileceğini göstermektedir. Ancak, Genetik Programlama Tümevarımsal Güven Aralığı metodu ile birlikte kullanılınca, yapılan tahminlerin sadece kısa vadede anlamlı sonuçlar ürettiği görülmüştür. Orta ve uzun vadeli yapılan tahminlerin anlamlı sonuçlar üretmediği görülmüştür.

Keywords

Yapay Zeka, Genetik Programlama, Güven Aralığı, Tahmin

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