Abstract
Weather pollution is considered as one of the most important, dangerous problem that affects our life and the society security from the different sides. The global warming problem affecting the atmosphere is related to the carbon dioxide emission (CO2) from the different fossil fuels along with temperature. In this paper, this phenomenon is studied to find a solution for preventing and reducing the poison CO2 gas emerged from affecting the society and reducing the smoke pollution. The developed model consists of four input attributes: the global oil, natural gas, coal, and primary energy consumption and one output the CO2 gas. The stochastic search algorithm Genetic Programming (GP) was used as an effective and robust tool in building the forecasting model. The model data for both training and testing cases were taken from the years of 1982 to 2000 and 2003 to 2010, respectively. According to the results obtained from the different evaluation criteria, it is nearly obvious that the performance of the GP in carbon gas emission estimation was very good and efficient in solving and dealing with the climate pollution problems.
Highlights
Weather state and condition is a very important and dangerous issue related to some views health, climate, agriculture, economics, and tourism
Different protocols and agreements were held between numerous countries to minimize the greenhouse gas emanation, such as the Kyoto protocol and the United Nations (UN) agreement that confirmed on the continuouspercentage checking and monitoring of the CO2 emission in the atmosphere to reduce it to the desired levels [3]
To solve the modeling problem for the carbon gas (CO2) estimation, we considered building a model structure that takes into the account the historical measurements of the carbon data during the previous years
Summary
Weather state and condition is a very important and dangerous issue related to some views health, climate, agriculture, economics, and tourism. Many researchers were attracted towards this type of problems due to its difficulty and challenges in considering different input variables that should be cautiouslyconsidered, studied and measured to build the accurate forecasting models. Climate pollution related to the carbon emission is a general serious world problem. The stochastic search algorithm Genetic Programming (GP) was used as an effective and powerful tool in building and estimating the forecasted model. The GP technique was applied to deal with important and dangerous phenomena that are the CO2 gas emitted based on four related inputs the global oil, natural gas (NG), coal, and primary energy (PE) consumption.
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