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Home / Archives / Volume-5 / Issue-3 / Article-7

Volume - 5 | Issue - 3 | september 2023

Sustainable Energy Transition: Analyzing the Impact of Renewable Energy Sources on Global Power Generation Open Access
Rahul Kumar Jha   69
Pages: 314-329
Cite this article
Jha, Rahul Kumar. "Sustainable Energy Transition: Analyzing the Impact of Renewable Energy Sources on Global Power Generation." Journal of Artificial Intelligence and Capsule Networks 5, no. 3 (2023): 314-329
Published
19 October, 2023
Abstract

This study delves into the intricate relationship between power plant attributes and electricity generation, employing data analysis and predictive modelling techniques. Through a comprehensive analysis of a global power plant dataset, critical factors such as plant capacity and commissioning year were identified as significant influencers on electricity generation. The research utilized correlation heatmaps to visually represent these relationships, offering valuable insights for policymakers and investors. A linear regression model was employed, leveraging capacity and commissioning year as features to predict electricity generation. The model's accuracy was evaluated using mean squared error, providing a quantitative measure of its predictive capabilities.

Keywords

Regression Machine Learning Predictive Analysis Correlation Heatmap Global Energy Data Data Cleaning

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