摘要
将诱导有序加权调和平均算子和马尔科夫链相结合,提出一种基于诱导有序加权调和平均算子和马尔科夫链的组合预测模型,该模型可以克服传统的组合预测方法赋予不变的权系数和以单一误差指标作为预测精度衡量的缺陷,同时采用马尔科夫链推出各单项预测模型在各个预测时间点预测精度的状态,从而得到组合模型的权系数。文中首先采用回归法、指数平滑法及灰色预测法分别建立了陕西省某市年用电量单项预测模型,随后引进诱导有序加权调和平均算子和马尔科夫链的概念,建立了年用电量的组合预测模型,并对年用电量进行了实证分析。实例分析表明了新模型能有效地提高组合预测精度,降低预测的风险性,从而证明这种组合模型具有较好的实用性。
This paper proposed a new combination forecasting model based on the Induced Ordered Weighted Harmonic Averaging （IOWHA） operator and Markov chain （MC） by combining the IOWHA operator and MC.The model can overcome some deficiencies in weighting and using single error index as forecasting precision measure of traditional combination forecasting model, meanwhile, by using of MC the forecasted accuracy condition of each forecasting method at the forecasted time point can be qualitatively surmised, thus its weight coefficient at the forecasted time point can be determined. This paper fwstly respectively makes use of Regression, Exponential Smoothing and Grey forecasting to construct models depending on annual electricity consumption of one city in Shaanxi Province. Secondly, the combination forecasting model of annual electricity consumption is founded by using the IOWHA operator and MC, and then the demonstration analysis about annual electricity consumption in future is gived. The example result illustrated that the new model can improve forecasting precision effectively. Therefore, the risk of forecasting is reduced. The results of the example shows that the combination model possesses better practicability.
出处
《电网与清洁能源》
2010年第9期38-43,共6页
Power System and Clean Energy
关键词
诱导有序加权调和平均算子
马尔科夫链
预测精度
组合预测
年用电量
Induced Ordered Weighted Harmonic Averaging （IOWHA） operator
Markov Chain （MC）
forecasting accuracy
combined forecasting
annual electricity consumption
