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.

DOI: 10.1504/IJGW.2019.097862

International Journal of Global Warming, 2019 Vol.17 No.2, pp.219 - 233

Received: 17 May 2018
Accepted: 04 Aug 2018
Published online: 20 Feb 2019 *

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