Almohammed, MustafaFarhan, Hameed MutlagNaseri, Raghad Awad SababanTürkben, Ayça Kurnaz2023-06-102023-06-102022Almohammed, M., Farhan, H. M., Naseri, R. A. S., & Turkben, A. K. (2022). Data mining and analysis for predicting electrical energy consumption. In 2022 International Conference on Artificial Intelligence of Things (ICAIoT). IEEE.https://hdl.handle.net/20.500.12939/3543In this research, data mining techniques that included the deep learning with different scenario is presented for predicting electrical energy consumption data. Energy of the features are implemented and calculated from the electrical energy consumption data. Different scenario with neuron numbers for artificial neural network are investigated and analyzed. Also the results are compared with other k-fold numbers of the data. The results of proposed method shows that the proposed methods has high accuracy and high performance.eninfo:eu-repo/semantics/closedAccessData Mining TechniquesElectrical Energy Consumption DataFeature AnalysisPredictingConference Object2-s2.0-85160536188N/A