A NOVEL ENERGY ACCOUNTING MODEL USING FUZZY RESTRICTED BOLTZMANN MACHINE RECURRENT NEURAL NETWORK / SARHANG SORGULI ; SUPERVISOR, PROF. DR. MEHMT AĞA

Yazar: Katkıda bulunan(lar):Dil: İngilizce 2023Tanım: 157 sheets ; 30 cm +1 CD ROMİçerik türü:
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Konu(lar): Tez notu: Thesis (PhD) - Cyprus International University. Institute of Graduate Studies and Research Business Administration Özet: Energy accounting is a system for regularly measuring, analyzing, and reporting the energy use of various activities. This is done to increase energy efficiency and monitor the impact of energy usage on the environment. Primary energy accounting is now done by determining the amount of fossil fuel energy required to generate it. However, if fossil fuels become scarcer, this strategy becomes less viable. Instead, a new energy accounting approach will be required, one that takes into consideration the intermittent character of the two most prevalent renewable energy sources, wind and solar power. Furthermore, estimation of the energy consumption data collected from household surveys, whether using a recall-based approach or a meter-based one, remains a difficult task. Hence, this paper proposes a novel energy accounting model using Fuzzy Restricted Boltzmann Machine-Recurrent Neural Network (FRBM-RNN). The energy consumption dataset is preprocessed using linear-scaling normalization. The proposed model is optimized using the Adaptive Fuzzy Adam Optimization Algorithm (AFAOA). The performance metrics like Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) are estimated. The estimated results for our proposed technique are MSE (0.19), RMSE (0.44), MAE (0.2), and MAPE (3.5).
Materyal türü: Thesis
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Materyal türü Geçerli Kütüphane Koleksiyon Yer Numarası Kopya numarası Durum Notlar İade tarihi Barkod Materyal Ayırtmaları
Thesis Thesis CIU LIBRARY Depo Tez Koleksiyonu D 440 S67 2023 (Rafa gözat(Aşağıda açılır)) C.1 Kullanılabilir Business Administration T3899
Suppl. CD Suppl. CD CIU LIBRARY Görsel İşitsel Tez Koleksiyonu D 440 S67 2023 (Rafa gözat(Aşağıda açılır)) C.1 Kullanılabilir Business Administration CDT3899
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Thesis (PhD) - Cyprus International University. Institute of Graduate Studies and Research Business Administration

Energy accounting is a system for regularly measuring, analyzing, and reporting the
energy use of various activities. This is done to increase energy efficiency and monitor
the impact of energy usage on the environment. Primary energy accounting is now
done by determining the amount of fossil fuel energy required to generate it. However,
if fossil fuels become scarcer, this strategy becomes less viable. Instead, a new energy
accounting approach will be required, one that takes into consideration the intermittent
character of the two most prevalent renewable energy sources, wind and solar power.
Furthermore, estimation of the energy consumption data collected from household
surveys, whether using a recall-based approach or a meter-based one, remains a
difficult task. Hence, this paper proposes a novel energy accounting model using Fuzzy
Restricted Boltzmann Machine-Recurrent Neural Network (FRBM-RNN). The energy
consumption dataset is preprocessed using linear-scaling normalization. The proposed
model is optimized using the Adaptive Fuzzy Adam Optimization Algorithm
(AFAOA). The performance metrics like Mean Square Error (MSE), Root Mean
Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage
Error (MAPE) are estimated. The estimated results for our proposed technique are
MSE (0.19), RMSE (0.44), MAE (0.2), and MAPE (3.5).

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