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.
Cyber Univ Korea, Dept Mech & Control Engn, 106 Bukchon Ro, Seoul 03051, South Korea
Recommended Citation:
Woo, Tae Ho. Global warming analysis for greenhouse gases impacts comparable to carbon-free nuclear energy using neuro-fuzzy algorithm[J]. INTERNATIONAL JOURNAL OF GLOBAL WARMING,2019-01-01,17(2):219-233