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Forecasting on Electricity Consumption of Tourism Industry in Changli County

机译:昌黎县旅游业电力消费预测

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In recent years, tourism become more popular, and analyzing electricity consumption in tourism industry contributes to its development. To predict energy consumption, this paper applies a new model, NEWARMA model, which means to add the variable's own medium- and long-term cyclical fluctuations item to the basic ARMA model, and the prediction accuracy will be significantly improved. This paper also compares fitting result of NEWARMA to neural network models and grey models, and finds that it performs better. Finally, through simulation analysis, this study finds that when electricity in one industry declines, other industries may be affected and changed too, which help our country to control total energy consumption in the society.
机译:近年来,旅游业变得更加流行,分析旅游业的电力消耗促进其发展。 为了预测能量消耗,本文采用新模型,新型号,这意味着将变量的自己的中期循环波动项添加到基本ARMA模型,并将显着提高预测精度。 本文还比较了Newarma到神经网络模型和灰色模型的拟合结果,并发现它表现得更好。 最后,通过仿真分析,本研究发现,当一个行业的电力下降时,其他行业也可能受到影响和变化,这有助于我们国家控制社会的总能耗。

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