Electrical Energy Demand Prediction: A Comparison Between Genetic Programming and Decision Tree

Ali DANANDEH MEHR; Farzaneh BAGHERİ; Mir Jafar Sadegh SAFARİ

doi:https://doi.org/10.35378/gujs.554463

Makale detayları

Electrical Energy Demand Prediction: A Comparison Between Genetic Programming and Decision Tree

Yazarlar:

Ali DANANDEH MEHR | Farzaneh BAGHERİ | Mir Jafar Sadegh SAFARİ

Yayıncı:

Gazi University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Gazi University Journal of Science 2020 Vol.33 Issue 1, pp.62-72

Belge Tipi:

Makale

Yayın Tarihi:

2/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000427854

eISSN:

2147-1762

DOI:

https://doi.org/10.35378/gujs.554463

Özet:

 


Several recent studies have used various data mining techniques to obtain accurate electrical energy demand forecasts in power supply systems. This paper, for the first time, compares the efficiency of the decision tree (DT) and classic genetic programming (GP) data mining models developed for electrical energy demand forecasting in Nicosia, Northern Cyprus. The models were trained and tested using daily electricity consumptions measured during the period 2011-2016 and were compared in terms of three statistical performance indices including coefficient of determination, mean absolute percentage error and concordance coefficient. The prediction results showed that the proposed models can be effectively applied to forecasts of electrical energy demand. The results also indicated that the GP is slightly superior to DT in terms of the performance indices.

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Makale detayları

Electrical Energy Demand Prediction: A Comparison Between Genetic Programming and Decision Tree

Yazarlar: Ali DANANDEH MEHR | Farzaneh BAGHERİ | Mir Jafar Sadegh SAFARİ

Yayıncı: Gazi University

Ana Başlıklar: Uygulamalı fizik

Dergi: Gazi University Journal of Science 2020 Vol.33 Issue 1, pp.62-72

Belge Tipi: Makale

Yayın Tarihi: 2/2020

Belge Dili: İngilizce

Document ID (Org No.): 2000427854

eISSN: 2147-1762

DOI: https://doi.org/10.35378/gujs.554463

Sayı

Yazarlar:

Ali DANANDEH MEHR | Farzaneh BAGHERİ | Mir Jafar Sadegh SAFARİ

Yayıncı:

Gazi University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Gazi University Journal of Science 2020 Vol.33 Issue 1, pp.62-72

Belge Tipi:

Makale

Yayın Tarihi:

2/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000427854

eISSN:

2147-1762

DOI:

https://doi.org/10.35378/gujs.554463