Büyük Menderes Akımlarının Frekans Tabanlı Tahmini

Abstract

Bu çalışmada, mevsimsel salınımlar gösteren, içsel bağımlı ve kaotik zaman serilerinin veriye dayalı tahmini için yeni bir yöntem önerilmektedir. Yöntem, gözlenmiş serilerdeki değer aralıklarının frekanslarına bağlı olarak mevcut verilerin zamansal ve niceliksel ilişkilerine dayalı olarak eksik veriler için tahminler üretmektedir. Frekans tabanlı tahmin adı verilen yöntem, genel bir yaklaşıma sahiptir ve test/onay/düzenleme/ağırlık katsayısı belirleme gibi işlemler yapılması gerekmemektedir. Geliştirilen yöntem, Büyük Menderes havzasındaki 34 istasyonun 9050 adet aylık toplam akım gözleminin tahmini ve 1210 adet eksik verinin tamamlanmasında kullanılmıştır. Gözlemler ve tahminler arasında tüm istasyonlar için elde edilen yüksek korelasyon değerleri, önerilen yöntemin akım verilerinin tahmininde başarılı olduğunu göstermektedir.

Keywords

• Frekans tabanlı tahmin,veriye dayalı modelleme,aylık toplam akım verileri,Büyük Menderes Havzası,eksik verilerin tamamlanması

Frequency Based Prediction of Büyük Menderes Flows

Abstract

In this study, a new method for the data driven prediction of interrelated and chaotic time series data showing seasonal fluctuations is proposed. The method produces predictions based on the temporal and quantitative relationships among the available data related with the frequencies of the value ranges of observed data. The method, which is called frequency based prediction, has a general approach and requires no testing/validation/adjustment/ weight determination steps. The developed method is used for predicting 9050 monthly total flow observations of 34 stations on Büyük Menderes River and for infilling 1210 missing data. High correlations obtained between the observations and predictions for all stations show that the proposed method is successful in the prediction of streamflow data.

Keywords

• Frequency based prediction,data-driven modeling,monthly total streamflow data,Büyük Menderes Basin,estimation of missing data

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