İklim değişikliğini azaltmak için bir emiter faaliyetinden kaynaklanan emisyon miktarını tahmin etmek için bulanık sistemin uygulanması

Understanding the connections between CO2 emissions regarding the fuel consumption and the climate change may assist countries to determine the amount of CO2 or CO2 equivalent emissions and act accordingly by re-formulating new policies regarding energy to reduce these emissions and achieving sustainable development. By creating a useful model using an adaptive neuro-fuzzy inference system (ANFIS) with multiple inputs, this research will serve as a foundation for future studies regarding other sectors responsible for CO2 or CO2 equivalent emissions, such as (industrial sector, agriculture, waste management, transportation, and other activities). This model will be able to predict the amount of emissions caused by vehicles. In this situation, the ANFIS model has been used along with prediction models based on actual data to forecast CO2 emissions based on three essential input indicators, engine size, number of cylinders, and fuel consumption, and correlate it with the amount of emissions.