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The aim of this work is to analyze factors influencing electricity consumption in Japan using regression analysis. Every season regression models are developed for forecasting and determining elasticity coefficient associated with climatic conditions. As explanation variables, we use temperature, relative humidity and other factors such us holidays. Then, several statistical tests, for instance, t-test,...
Traditional time series forecasting models are difficult to capture the nonlinear patterns. Support vector regression (SVR) is a powerful tool for modeling the inputs and output(s) of complex and nonlinear systems. However, parameters determination for a SVR model is competent to the forecasting accuracy. Several evolutionary algorithms, such as genetic algorithms and simulated annealing algorithms...
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