![]() Big Data Cogn Comput 2(10):1–18Īyyad S, Saleh A, Labib L (2019a) A new distributed feature selection technique for classifying gene expression data. In: Proceedings of the 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies, Manchester, pp 1–7Ītlam H, Walters R, Wills G (2018) Fog computing and the internet of things: a review. J Big Data 6(109):1–14Īrnold M, Rui H, Wellssow W (2011) An approach to smart grid metrics. IEEE, Riyadh, pp 1–7Īnsari M, Vakili V, Bahrak B (2019) Evaluation of big data frameworks for analysis of smart grids. In: Proceedings of the 2017 International Conference on Informatics, Health & Technology (ICIHT). IEEE Access 5:9131–9138Īlyam R, Alhajja J, Alnajran B, Elaalam I, Alqahtan A, Aldhaffer N, Owolab T, Olatun S (2017) Investigating the effect of correlation based feature selection on breast cancer diagnosis using artificial neural network and support vector machines. ![]() Pac Sci Rev A Nat Sci Eng 18(2):123–127Īlrawais A, Alhothaily A, Hu C, Xing X, Cheng X (2017) An attribute-based encryption scheme to secure fog communications. ![]() Alex Eng J 57(1):223–233Īli D, Yohanna M, Puwu M, Garkida B (2016) Long-term load forecast modelling using a fuzzy logic approach. In: Proceedings of the 2019 International Conference on Computer and Information Sciences (ICCIS).Īli D, Yohanna M, Ijasini P, Garkida M (2018) Application of fuzzy – Neuro to model weather parameter variability impacts on electrical load based on long-term forecasting. Energy Rep 4:91–100Īl Yami M, Schaefer D (2019) Fog computing as a complementary approach to cloud computing. Finally, this paper covers the analysis of the load prediction phase in ELF strategy in which the prediction techniques will be reviewed.Īkhavan-Hejazi H, Mohsenian-Rad H (2018) Power systems big data analytics: an assessment of paradigm shift barriers and prospects. Feature selection and outlier rejection are discussed as a preprocessing process to filter the data, and then the load prediction process is explained. Additionally, the different techniques used to manage big data generated by sensors and meters for application processing are explored. Furthermore, many classification methods and then electrical load forecasting (ELF) strategy that includes the preprocessing phase and the prediction phase have been discussed. A brief overview of IoT technologies is provided. It will explore the architectural structure of a typical IoT, cloud computing system, and different levels of the system. Most of the basic concepts affect such new technology like (Internet of Things (IoT), fog, cloud computing, and big data analysis) are discussed. ![]() In this paper, a comprehensive survey on SEG as a new technology and operating models which will affect performance of distribution networks in the future are explored in detail. Hence, SEG is considered as the next generation power grid. Under different uncertainties, SEG is capable of self-healing, adaptive, resilient, and sustainable with foresight for prediction. The smart electrical grid (SEG), that utilizes information for creating a widely distributed automated energy delivery network, is considered as an advanced digital 2-way power flow power system. ![]()
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