Global warming analysis for greenhouse gases impacts comparable to carbon-free nuclear energy using neuro-fuzzy algorithm Online publication date: Wed, 20-Feb-2019
by Tae Ho Woo
International Journal of Global Warming (IJGW), Vol. 17, No. 2, 2019
Abstract: As one of energy characteristics, the importance of climate effects has been increasing due to the side-effect such as the drought, flood, heavy snow and so on. The nonlinear artificial intelligence can be reasonably applied in the analysis of the simulations, because the human-brain mimicking algorithm can show the practicable results. Basically, the quantifications in the study results are based on the randomly generated numbers where the Monte Carlo methods are applied. The Boolean numbers are generated in the variable constructions. Furthermore, there are multiplications in population which are decided by the expert judgments. The causes loops for CO2 and temperature are obtained. In addition, there is the result of variable albedo vs. normalised temperature with dimensionless values. Global collaboration can prepare and control the global warming as the geological scale aspect as well as the collaborated idea utilisation that can develop the carbon minimising technology and green energy development.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Global Warming (IJGW):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook