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  • Volume 2014

    G M (1, 1) Analysis and Forecasting for Efficient Energy Production and Consumption
    (International Journal of Business, Economics and Management Works)

    Vol. 1, Issue 1, PP. 6-11, Nov. 2014
    Keywords: Grey Models, Auto Regressive Moving Average, Model accuracy, Electricity Demands

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    Abstract

    Electricity Generation and Forecasting is prerequisite to enhance industrialization, farming and residential requirement of one’s nation. It has great impact on both nation’s economy and standard of living that can be achieved through new forecasting techniques, enhanced electricity generation methodologies and better electricity conservation techniques. Most of the countries are allocating significant amount for power generation and forecasting from nation’s annual budgets. Much research work has been carried out to analyze and propose innovative methodologies for efficient electricity generation and forecasting. In our approach, Grey Model (1, 1) based on grey system has been used for forecasting results. Performance of the proposed technique has been compared with existing Auto regressive moving average forecasting model. Annual power generation and forecasting data in Sri Lanka were used as our case study. Unexpected power demands with non-systematic behaviour patterns motivate to use GM (1, 1) models. MAPE (Mean absolute percentage error), MSD (Mean absolute deviation) and MSE (Mean squared error) accuracy testing result shows that GM (1, 1) is outperformed compared with model fitting and model forecasting.  

    Author

    1. R.M. Kapila Taranga Ratnayaka: School of Economics, Wuhan University of Technology, Wuhan, PR China, kapila.tr@gmail.com
    2. D.M Kumudu Nadeeshani Seneviratna: School of Economics, Wuhan University of Technology, Wuhan, PR China, kseneviratna@gmail.com  

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    Cite

    R.M. Kapila Tharanga Rathnayaka, D.M Kumudu Nadeeshani Seneviratna "G M (1, 1) Analysis and Forecasting for Efficient Energy Production and Consumption" International Journal of Business, Economics and Managment works, Vol. 1, Issue 1, PP. 6-11, Nov. 2014

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