An Intelligent System for the Evaluation of Climate Change Effects on the Environment.

A large amount of processes, which are physical, chemical and biological, are related to the global climate, which is the main component of climate change. These processes transform the global environment into a complicated situation. Climate change is the most large-scale and wellknown vexed question. This paper presents a Fuzzy Inference System (FIS) to predict the relationship between the causes and effects of climate change. Here, CO2 (Carbon Dioxide), Global Temperature Changes, Snow Cover, Percentage of Forestlands, Natural Forces, and Net Radiation are considered as important factors and FIS inputs while the considered FIS outputs are: Ozone Layer Changes, Arctic Ice Sheet Level, Permafrost Level, and Sea Level. The proposed FIS is tested on realistic scenarios and the results are in agreement with results from other authors' approaches. However, the use of a FIS allows to include elements of uncertainty and vagueness in the input variables considered. [ABSTRACT FROM AUTHOR]