Forecasting of nuclear energy trends in Romania using XGBoost

Suman Chowdhury, Dilip Kumar Das

Abstract


The energy demand continues to rise due to the exponential growth of the world's population. In today's world, every aspect of life, including industry, education, household, transport, and healthcare, relies on energy. Generating power in an environmentally friendly manner is a major concern. Predicting nuclear energy production depends on various factors. Researchers used the extreme gradient boost (XGBoost) machine learning algorithm for prediction. The study revealed that the RMSE validation value is 25.10810, while the training value is 15.01759 after 2000 iterations. According to the study, Romania has the potential to produce 1,300 MW of electricity in a single day through nuclear energy. Nuclear energy production can be a viable solution for decarburization and meeting energy needs. The prompt of nuclear energy in the present world is harnessing to the utmost level so that energy crisis can be mitigated for a long run. This paper tries to show the potentiality of nuclear energy in Romania predicting the future trends with the help of time series analysis.

Keywords


Climate change; Fossil fuel; Net-zero emission; Nuclear energy; Renewable energy; XGBoost

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DOI: http://doi.org/10.11591/ijeecs.v40.i1.pp78-84

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES).

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