https://doi.org/10.1140/epjs/s11734-024-01220-4
Regular Article
A comparative study of simulink fuzzy inference system time series method and traditional time series methods for forecasting the air quality index
Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai Campus, 600127, Chennai, Tamil Nadu, India
Received:
13
March
2024
Accepted:
17
June
2024
Published online:
27
June
2024
The primary objective of this paper is to conduct a comparative analysis between simulink fuzzy inference system (FIS) time series analysis and traditional time series analysis to highlight the importance of simulink FIS time series analysis in enhancing model performance. This paper mainly focuses on forecasting the air quality index for the next 7 days based on gathered data through a novel approach to time series analysis by employing the simulink regression output of a FIS. The study emphasises the significance of adjusting the membership function and parameters in the FIS simulation model as hyper-tuning parameters, leading to enhanced accuracy in the time series model. Validation is performed using measures such as RMSE, MSE, MAE, and MaxDeviation.
Mathematics Subject Classification: 93C42 / 03B52 / 62M10
K. M. Ordenshiya and G. K. Revathi contributed equally to this work.
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