ANALYZING COAL CONSUMPTION IN CHINA: FORECASTING WITH THE ECFGM(1, 1) MODEL AND A PERSPECTIVE ON THE FUTURE

Ümmügülsüm Erdinç; Halis Bilgil

Article Details

ANALYZING COAL CONSUMPTION IN CHINA: FORECASTING WITH THE ECFGM(1, 1) MODEL AND A PERSPECTIVE ON THE FUTURE

Authors:

Ümmügülsüm Erdinç | Halis Bilgil

Publisher:

Giresun University

Main Topics:

Time-Series Analysis | Statistical Analysis

Journal:

Turkish Journal of Forecasting Vol.8 Issue 2, pp.45-53

Document Type:

Article

Publication Date:

9/2024

Document Language:

English

Document ID (Org No.):

2001327054

pISSN:

2618-6594

Keywords:

Abstract:

 The study analyzes coal consumption using the ECFGM1, 1 model by utilizing time series data provided by the Statistical Review of World Energy for the years 2016-2019. The optimal α value, determined using the Brute Force Algorithm, is utilized to establish the models parameters and formulate the solution function. Subsequently, the models predictive accuracy is assessed using data from the years 2020-2022, with the resulting Mean Absolute Percentage Error MAPE reflecting the models overall performance.

 The study analyzes coal consumption using the ECFGM1, 1 model by utilizing time series data provided by the Statistical Review of World Energy for the years 2016-2019. The optimal α value, determined using the Brute Force Algorithm, is utilized to establish the models parameters and formulate the solution function. Subsequently, the models predictive accuracy is assessed using data from the years 2020-2022, with the resulting Mean Absolute Percentage Error MAPE reflecting the models overall performance.

 The study analyzes coal consumption using the ECFGM1, 1 model by utilizing time series data provided by the Statistical Review of World Energy for the years 2016-2019. The optimal α value, determined using the Brute Force Algorithm, is utilized to establish the models parameters and formulate the solution function. Subsequently, the models predictive accuracy is assessed using data from the years 2020-2022, with the resulting Mean Absolute Percentage Error MAPE reflecting the models overall performance.

 The study analyzes coal consumption using the ECFGM1, 1 model by utilizing time series data provided by the Statistical Review of World Energy for the years 2016-2019. The optimal α value, determined using the Brute Force Algorithm, is utilized to establish the models parameters and formulate the solution function. Subsequently, the models predictive accuracy is assessed using data from the years 2020-2022, with the resulting Mean Absolute Percentage Error MAPE reflecting the models overall performance.

Article Details

ANALYZING COAL CONSUMPTION IN CHINA: FORECASTING WITH THE ECFGM(1, 1) MODEL AND A PERSPECTIVE ON THE FUTURE

Authors:

Ümmügülsüm Erdinç | Halis Bilgil

Publisher:

Giresun University

Main Topics:

Time-Series Analysis | Statistical Analysis

Journal:

Turkish Journal of Forecasting Vol.8 Issue 2, pp.45-53

Document Type:

Article

Publication Date:

9/2024

Document Language:

English

Document ID (Org No.):

2001327054

pISSN:

2618-6594

Coal consumption

ECFGM(1, 1)

Brute Force algorithm

Issues

Article Details

ANALYZING COAL CONSUMPTION IN CHINA: FORECASTING WITH THE ECFGM(1, 1) MODEL AND A PERSPECTIVE ON THE FUTURE

Authors: Ümmügülsüm Erdinç | Halis Bilgil

Publisher: Giresun University

Main Topics: Time-Series Analysis | Statistical Analysis

Journal: Turkish Journal of Forecasting Vol.8 Issue 2, pp.45-53

Document Type: Article

Publication Date: 9/2024

Document Language: English

Document ID (Org No.): 2001327054

pISSN: 2618-6594

Coal consumption

ECFGM(1, 1)

Brute Force algorithm

Issues

Authors:

Ümmügülsüm Erdinç | Halis Bilgil

Publisher:

Giresun University

Main Topics:

Time-Series Analysis | Statistical Analysis

Journal:

Turkish Journal of Forecasting Vol.8 Issue 2, pp.45-53

Document Type:

Article

Publication Date:

9/2024

Document Language:

English

Document ID (Org No.):

2001327054

pISSN:

2618-6594