A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production

Yıl: 2019 Cilt: 23 Sayı: 2 Sayfa Aralığı: 635 - 646 Metin Dili: İngilizce DOI: DOI: 10.19113/sdufenbed.494396 İndeks Tarihi: 23-10-2020

A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production

Öz:
Over the last decades, Turkey pays special attention to electricity productionto afford its needs. Researchers applied different methodologies including statisticalbased and artificial intelligence-based to correctly predict the future amount of electricityproduction, consumption, and demand. However,limited researchers focused on Turkey’selectricity production prediction problem as a time series analysis. For this reason, wetackle this problem by considering it as a time series analysis in this study. We haveused different methods including traditional machine learning algorithms Support VectorRegression (SVR) and Multilayer Perceptrons (MLP) and a deep learning algorithm LongShort-Term Memory (LSTM) to create a better model for Turkey monthly electricityproduction dataset. Based on our findings LSTM outperforms SVR and MLP approachesin terms of commonly used statistical error evaluation metrics
Anahtar Kelime:

Zaman Serileri Tahminlenmesinde Makine Ögrenimi ve Derin Ögrenme Tekniklerinin ˘ Kıyaslanması: Türkiye Elektirik Üretimi için En Iyi Tahmin Modelinin Seçilmesine Yönelik Bir Vaka Çalısması

Öz:
Son yıllarda Türkiye ihtiyaçlarını kar¸sılayabilmek adına elektrik üretimine yogun bir sekilde dikkat vermektedir. Ara¸stırmacılar elektrik üretim, tüketim ve talep mikarını dogru bir sekilde tahmin etmek için istatistik ve yapay zeka tabanlı yöntemleride içerenbirçok farklı metod uygulamıslardır. Sınırlı sayıda ara¸stırmacı Türkiye’nin elektrik üretim tahminleme problemini bir zaman serisi analizi olarak irdelemistir. Bu nedenle bu çalısmada söz konusu problem zaman serileri analizi olarak ele alınmıstır. Bu açıdan çalısmada hem Destek Vektör Makineleri (DVM) ve Çok Katmanlı Nöronlar (ÇKN) gibi klasik makine ögrenimi yöntemleri hem de Uzun Kısa Dönemli Hafıza (UKDH) yöntemigibi derin ögrenme yöntemi Türkiye’nin üretmesi gereken aylık elektrik üretim miktarınıtahmin etmek için kullanılmıstır. Çalısmanın bulgularına dayalı olarak derin ögrenmealgoritması istatistiksel hata oranlarına göre diger klasik makine ögrenimi yöntemlerindendaha basarılı sonuçlar vermektedir.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
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APA ÜNLÜ R (2019). A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. , 635 - 646. DOI: 10.19113/sdufenbed.494396
Chicago ÜNLÜ Ramazan Erkin A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. (2019): 635 - 646. DOI: 10.19113/sdufenbed.494396
MLA ÜNLÜ Ramazan Erkin A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. , 2019, ss.635 - 646. DOI: 10.19113/sdufenbed.494396
AMA ÜNLÜ R A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. . 2019; 635 - 646. DOI: 10.19113/sdufenbed.494396
Vancouver ÜNLÜ R A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. . 2019; 635 - 646. DOI: 10.19113/sdufenbed.494396
IEEE ÜNLÜ R "A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production." , ss.635 - 646, 2019. DOI: 10.19113/sdufenbed.494396
ISNAD ÜNLÜ, Ramazan Erkin. "A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production". (2019), 635-646. https://doi.org/DOI: 10.19113/sdufenbed.494396
APA ÜNLÜ R (2019). A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 23(2), 635 - 646. DOI: 10.19113/sdufenbed.494396
Chicago ÜNLÜ Ramazan Erkin A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 23, no.2 (2019): 635 - 646. DOI: 10.19113/sdufenbed.494396
MLA ÜNLÜ Ramazan Erkin A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol.23, no.2, 2019, ss.635 - 646. DOI: 10.19113/sdufenbed.494396
AMA ÜNLÜ R A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2019; 23(2): 635 - 646. DOI: 10.19113/sdufenbed.494396
Vancouver ÜNLÜ R A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi. 2019; 23(2): 635 - 646. DOI: 10.19113/sdufenbed.494396
IEEE ÜNLÜ R "A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production." Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 23, ss.635 - 646, 2019. DOI: 10.19113/sdufenbed.494396
ISNAD ÜNLÜ, Ramazan Erkin. "A Comparative Study of Machine Learning and Deep Learning for Time Series Forecasting: A Case Study of Choosing the Best Prediction Model for Turkey Electricity Production". Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 23/2 (2019), 635-646. https://doi.org/DOI: 10.19113/sdufenbed.494396