Abstract
The greenhouse effect related global warming is studied by the artificial intelligence (AI) based neural networking modelling. The stochastic impacts by regression on population, affluence and technology (STIRPAT) model is applied to the carbon dioxide gas based greenhouse effect. It is shown of the energy factor where four sources as oil, coal, nuclear, and renewable are connected in which the values are cumulative for comparisons with nuclear energy. The values are higher in the case of 'without nuclear'. The highest values are 1,808.78 and 6,609.68 respectively which are dimensionless and means for the global warming effectiveness. It is also described as the global warming factor for comparisons with nuclear power in which the values show higher in the later time. The study shows the dynamical transients of the negative effects in the case of the nuclear energy portion missing. Therefore, the effect of the nuclear part should be considered as one of major energy sources of a nation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
