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This research aims to analyze the efficiency of triangular and trapezoidal membership functions in forecasting CO2, N2O, and CH4 emissions in Indian smart cities. Over 10-years, emissions data for these gases were collected and used to determine membership values for both functions. The study evaluated the performance of the membership functions using Root Mean Square Error (RMSE) values and percentage error analysis. The results indicated that the trapezoidal membership function provided more accurate results for CO2 and CH4 emissions, while the triangular membership function was more accurate for N2O emissions. These findings highlight the importance of selecting appropriate membership functions tailored to specific gases to enhance emission forecast accuracy. The study emphasizes the significance of such insights for decision-makers, urban planners, and environmental agencies involved in emissions reduction measures and smart city development. However, further research is recommended to validate these findings and explore additional factors that may influence the performance of membership functions in emission prediction in smart cities. In conclusion, this project offers a comprehensive analysis of triangular and trapezoidal membership functions’ accuracy in predicting emissions in Indian smart cities, emphasizing the crucial factors.
Sivasubramanian et al. (Wed,) studied this question.