Modeling of CO2 Emission Statistics in Turkey by Fuzzy Time Series Analysis

Fatih Cemrek
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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. The RMSE value was taken into consideration to determine the most suitable model among the analysis performed.
用模糊时间序列分析建立土耳其二氧化碳排放统计模型
确定时间序列将来将接收到的值的过程是一个非常重要的概念。模糊时间序列方法由于更便于处理不完整或不明确的小样本数据,并且不包含对时间序列的任何假设,近年来得到了广泛的应用。本研究采用模糊时间序列分析法预测土耳其的CO2排放值。为此,分析了1990年至2016年各部门温室气体排放总量(CO2当量)的时间序列(年度)。本研究的主要目的是利用模糊时间序列分析对土耳其的温室气体排放统计数据进行建模。考虑RMSE值,以确定在执行的分析中最合适的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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