GMDH-type neural network-based monthly electricity demand forecasting of Turkey
نویسندگان
چکیده
In this study, it was aimed to develop an accurate forecasting model for the monthly electricity demand of Turkey in medium-term. For purpose, Group Method Data Handling (GMDH)-type Neural Network (NN) approach used structure a nonlinear time-series based model. A large dataset containing considered period 2003-2018. The developed tested 2019/01-2019/11 order determine generalization ability test results showed that very close actual values. obtained performances were 2.10 % mean absolute percentage error (MAPE), 2.36 root square (RMSPE) and 0.869 coefficient determination (R2). addition, proposed GMDH-type NN compared with literature study. comparison revealed better Turkey. Finally, utilized forecast 2019/12-2020/12.
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ژورنال
عنوان ژورنال: International advanced researches and engineering journal
سال: 2021
ISSN: ['2618-575X']
DOI: https://doi.org/10.35860/iarej.766762