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                <text>In modern technology and systems modeling, electric energy forecasting is extremely vital in gaining effective application of energy policies. This model is formulated after a thorough study of the power load conditions of Ghana as well as the factors that affect domestic electricity demand of supply in the Country was conducted. In Ghana, the LEAP (Long-range Energy Alternatives Planning) forecast model is officially applied for electricity demand and projection of power supply which comes with forecasting errors. Thus, there exists a crucial need to develop a forecasting model for the best energy policies formulation and consequent minimization of overall forecasting error compared to the LEAP model. Results from the quantitative classical multiplicative decomposition forecast model is comparatively precise with a reduced forecast error margin between− 5–4.5% compared to an existing prediction error margin viz., 1% to-11%.</text>
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                <text>In modern technology and systems modeling, electric energy forecast is extremely vital for the attainment of effective application of energy policies. This model is formulated after a thorough study of the power load conditions of Ghana and the factors that affect domestic electricity demand and supply in the country was conducted. In Ghana, the Long-range Energy Alternatives Planning (LEAP) forecast model is officially applied for electricity demand and projection of power supply which comes with forecasting errors. Thus, there exists a crucial need to develop a forecasting model for the best energy policies formulation and consequent minimization of overall forecasting error compared to the LEAP model. A step-by-step mathematical approach of forecasting time series data of all the domestic electricity demand areas of Accra, namely: Mallam, Achimota and Accra East 9-year data was applied in the forecasting …</text>
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                <text>Energy in all forms is a key requirement for human livelihoods and socio-economic development. However, overreliance on a single sthece of energy can cause energy management issues because of the occurrence of system over-burdening. Thus, the utilization of other forms of energy is highly promoted worldwide, with a clear emphasis on enhancing environmentalism and reducing pollution through waste management and control. This paper considers the use of digital image processing in the form of pattern recognition to extract the pattern of a coconut shell and charcoal wood to show the correlation between their patterns and thus deduce the energy properties of the coconut shell.</text>
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