Forecasting electricity consumption in Algeria using artificial neural networks

المؤلفون المشاركون

Shukri, Sidi Muhammad
Sahid, Abd al-Qadir

المصدر

Economic Visions Review

العدد

المجلد 12، العدد 1 (30 يونيو/حزيران 2022)، ص ص. 247-261، 15ص.

الناشر

جامعة الشهيد حمه لخضر-الوادي كلية العلوم الاقتصادية و التجارية و علوم التسيير

تاريخ النشر

2022-06-30

دولة النشر

الجزائر

عدد الصفحات

15

التخصصات الرئيسية

الاقتصاد و التجارة

الموضوعات

الملخص EN

This paper applied the artificial neural network (ANN) to forecast electricity consumption in Algeria.

two independent variables, GDP (gross domestic product) per capita and population, are used to forecast electricity consumption.

the models' performance is evaluated using the coefficient of determination (R2) and the mean absolute percentage error (MAPE).

the results show that the ANN model that models electricity consumption as a function of economic indicators outperforms the ANN time input model.

in addition, the results indicate that Algeria’s projected electricity consumption will be 76.06 and 94.66 billion kwh in 2020 and 2025, respectively.

as a result, improved electricity forecasting is critical for policymakers when constructing future energy plants.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Shukri, Sidi Muhammad& Sahid, Abd al-Qadir. 2022. Forecasting electricity consumption in Algeria using artificial neural networks. Economic Visions Review،Vol. 12, no. 1, pp.247-261.
https://search.emarefa.net/detail/BIM-1424132

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Shukri, Sidi Muhammad& Sahid, Abd al-Qadir. Forecasting electricity consumption in Algeria using artificial neural networks. Economic Visions Review Vol. 12, no. 1 (Jun. 2022), pp.247-261.
https://search.emarefa.net/detail/BIM-1424132

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Shukri, Sidi Muhammad& Sahid, Abd al-Qadir. Forecasting electricity consumption in Algeria using artificial neural networks. Economic Visions Review. 2022. Vol. 12, no. 1, pp.247-261.
https://search.emarefa.net/detail/BIM-1424132

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes appendices : p. 255-261

رقم السجل

BIM-1424132