MODELING OF CO2 EMISSION STATISTICS in TURKEY BY FUZZY TIME SERIES ANALYSIS

Year 2023, Volume: 24 Issue: 1, 35 - 47, 29.03.2023

Fatih Çemrek

https://doi.org/10.18038/estubtda.1197724

Abstract

The process of determining the values which a time series will receive in the future is a very important concept. The fuzzy time series method has been widely used in recent years as it is more convenient to process data in small samples which are incomplete and/or ambiguous, and it does not contain any assumptions for time series. In this study, fuzzy time series analysis was used to predict CO2 emission values for Turkey. For this purpose, time series (annual) for total greenhouse gas emissions by sectors (CO2 equivalent) between 1990 and 2016 were analyzed. The main goal of this study is to model greenhouse gas emission statistics in Turkey with fuzzy time series analysis.

Keywords

Time Series Analysis, Fuzzy Time Series Analysis, CO2 emission, RMSE, Chen Models, Gustafson-Kessel clustering algorithm

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