Title: Global warming analysis for greenhouse gases impacts comparable to carbon-free nuclear energy using neuro-fuzzy algorithm
Authors: Tae Ho Woo
Addresses: Department of Mechanical and Control Engineering, The Cyber University of Korea, 106 Bukchon-ro, Jongno-gu, Seoul 03051, South Korea
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.
Keywords: global warming; neuro-fuzzy; nuclear energy; artificial intelligence.
International Journal of Global Warming, 2019 Vol.17 No.2, pp.219 - 233
Available online: 15 Feb 2019 *Full-text access for editors Access for subscribers Purchase this article Comment on this article