Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Citation - Scopus: 59A Hybrid Forecasting Model Using LSTM and Prophet for Energy Consumption with Decomposition of Time Series Data(PeerJ Inc., 2022) Arslan, SerdarArticle Citation - WoS: 37Citation - Scopus: 59A Hybrid Forecasting Model Using Lstm and Prophet for Energy Consumption With Decomposition of Time Series Data(Peerj inc, 2022) Arslan, SerdarFor decades, time series forecasting had many applications in various industries such as weather, financial, healthcare, business, retail, and energy consumption forecasting. An accurate prediction in these applications is a very important and also difficult task because of high sampling rates leading to monthly, daily, or even hourly data. This high-frequency property of time series data results in complexity and seasonality. Moreover, the time series data can have irregular fluctuations caused by various factors. Thus, using a single model does not result in good accuracy results. In this study, we propose an efficient forecasting framework by hybridizing the recurrent neural network model with Facebook's Prophet to improve the forecasting performance. Seasonal-trend decomposition based on the Loess (STL) algorithm is applied to the original time series and these decomposed components are used to train our recurrent neural network for reducing the impact of these irregular patterns on final predictions. Moreover, to preserve seasonality, the original time series data is modeled with Prophet, and the output of both sub-models are merged as final prediction values. In experiments, we compared our model with state-of-art methods for real-world energy consumption data of seven countries and the proposed hybrid method demonstrates competitive results to these state-of-art methods.Article Citation - WoS: 4Citation - Scopus: 6Et ve Balık Eti Hanehalkı Talebinin Mevsimselliği: Bir Kentsel Alan Örneği(Tubitak Scientific & Technological Research Council Turkey, 2005) Klasra, Mushtaq Ahmad; Fidan, HalilBu çalışma, Almost Ideal Demand System (AIDS)'i kullanarak, farklı mevsimlerde et ve balık için hane halkı talebine etkili faktörlerin tahmininde çıkarımlarda bulunmaktadır. Anket verileri kullanılarak, bütçe payı, talebin fiyat elastikiyeti, çapraz elastikiyet ve balık ve et için harcamalar, eşitlikler sistemi ile tahmin edilmiştir. Özellikle, Kurban Bayramı dönemlerinde bütçe paylarında artış olması durumu et ve balık tüketiminin mevsimsel etkisini inceleyen bu çalışmanın temel sonucu olmuştur. Bunun ötesinde, kentsel alanda yaşayan insanlar, hamsi hariç, fiyat artışlarına karşı duyarlı oldukları bulunamamıştır. Bu çalışma, politika yapıcıları, üreticiler ve pazarlama uzmanlarının izleyecekleri politikalarda etkili kaynak kullanımlarının düzenlenmesine, bu sonuçların onlara yardımcı olabilmesi bakımından önemlidir.