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Forecasting of Coal Consumption Using an Artificial Neural Network and Comparison with Various Forecasting Techniques

S, Jebaraj and S, Iniyan and R, Goic (2011) Forecasting of Coal Consumption Using an Artificial Neural Network and Comparison with Various Forecasting Techniques. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects .

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Abstract

The forecasting of energy consumption is essential for any country to study its future energy demand and to formulate necessary government policies. This article presents the formulation of forecasting models for the prediction of coal consumption in various sectors, such as domestic, transportation, power, and other sectors including the total coal consumption in India. A new system of forecasting a model based on the artificial neural network (univariate and multivariate) has been developed, which is a refinement on the classical time series models. The objective of the present work is to formulate the neural network model to forecast coal consumption and to compare it with the regression models. The forecast of total coal consumption in India for the years 2010, 2020, and 2030 was predicted to be 695,518, 890,143, and 1,594,844 thousand tons, respectively. The actual coal consumption data is used to validate the different forecasting models and it is found that the artificial neural network model gives better results in most of the cases.

Item Type:Article
Academic Subject One:Energy
Departments / MOR / COE:Departments > Mechanical Engineering
ID Code:11686
Deposited By: Dr Jebaraj Sargunam Azariah
Deposited On:08 Sep 2015 03:52
Last Modified:08 Sep 2015 03:52

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