Using Machine Learning to Predict the Effect of Non-renewable Energy Sources on Climate Change in India

Resource type
Report
Authors/contributors
Title
Using Machine Learning to Predict the Effect of Non-renewable Energy Sources on Climate Change in India
Abstract
Chapter 5 makes an attempt to predict trends in average land temperature due to CO2 emissions from all the non-renewable energy resources like “coal”, “oil”, “natural gas”, and “flaring”. The chapter illustrates the step-by-step process of time series analysis that is used to forecast temperature values. Predictions with the help of a machine learning model reveal that if no significant and immediate steps are implemented, emissions from these sources of energy will continue to rise in the near future at the current rate of consumption and production. The findings indicate that the average land temperature in India is predicted to rise by 0.2 degrees Celsius in the coming years.
Date
2022-09-17
Call Number
openalex: W4296193082
Extra
DOI: 10.1007/978-981-19-5244-9_5 openalex: W4296193082
Citation
Sharma, N., & De, P. K. (2022). Using Machine Learning to Predict the Effect of Non-renewable Energy Sources on Climate Change in India. https://doi.org/10.1007/978-981-19-5244-9_5