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航空公司能耗的预测直接影响能源需求的规划与节能的决策。针对航空公司能耗数据既有趋势性又有波动性的特点,提出了新陈代谢灰色马尔科夫-ARMA的能耗组合滑动预测模型。该模型利用灰色马尔科夫方法描述了能耗的变动趋势,通过ARMA模型捕捉残差序列的相关性来描述波动性,用新陈代谢的方法剔除模型中失去时效性的旧数据,解决了常规预测模型不足以完全描述航空公司能耗运动趋势的问题,提高了模型预测精度。仿真结果表明:提出模型精度优于传统ARMA模型和灰色马尔科夫模型,能够实现月度能耗的有效预测,为航空公司能耗监测和节能工作的优化开展提供了有力支持。
Airline projections of energy consumption have a direct impact on energy demand planning and energy saving decisions. Aiming at the characteristics of both the trend and the volatility of airlines’ energy consumption data, the energy consumption sliding forecasting model based on metabolic gray Markov-ARMA is proposed. The model describes the trend of energy consumption by using gray Markov method, describes the volatility by capturing the relativity of residual sequences by using ARMA model, eliminates the old data with the loss of timeliness in the model by using the metabolic method, and solves the problems of conventional prediction model Not enough to fully describe the air energy movement trend of the problem, improve the model prediction accuracy. The simulation results show that the proposed model accuracy is superior to the traditional ARMA model and the gray Markov model, which can effectively predict monthly energy consumption and provide strong support for the optimization of airlines’ energy consumption monitoring and energy conservation.