The Role of Machine Learning in Supporting the Decision in Power Sector-COMESA’s Region-Sudan

Nessreen Abdelfatah Ali Abdoun; Khaled Mafouz

doi:10.59573/emsj.8(6).2024.21

Authors

Nessreen Abdelfatah Ali Abdoun
Khaled Mafouz

DOI:

https://doi.org/10.59573/emsj.8(6).2024.21

Keywords:

Machine Learning, Power sector, Weka software, Data Mining, Business Model

Abstract

According to the huge amount of data generated by the power sector around the world and the challenges facing power sectors in Africa, this work provides a review of the existing situation in the power sector in Sudan as part of COMESA's region. Data mining and analytics have played an important role in knowledge discovery and decision-making in the process of the proposed reform and recovery strategy for the power sector in Sudan using ML techniques for information extraction, data pattern recognition that can handle the increase of the data. This work also presents the advantages of the Weka tool in making decisions regarding the ideal power generation projects according to the type of fuel and technologies and the installed capacity. It also gives a clear idea about the suitable business model for the sector to perform the required assignment that helps to achieve the purpose of the actions that should be implemented to support the power sector in Sudan.

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