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Prediction of Water Consumption in Hospitals Based on a Modified Grey GM (0, 1∣sin) Model of Oscillation Sequence: The Example of Wuhan City

机译:基于改进的灰色GM(0,1∣sin)振荡序列模型的医院用水预测-以武汉市为例

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Water shortage is one of the main factors limiting urban construction and development. Scientific forecasting of water consumption is an important approach for the rational allocation of water resources. Taking the hospitals in Wuhan City as an example and basing the analysis on the characteristics of actual water consumption, we proposed a modified grey GM (0, 1∣sin) model of oscillation sequence. Using the grey theory, the variable weight-strengthening buffer operator (VWSBO) was introduced into this model to weaken the interference of the disturbance term on the data sequence. The actual quarterly total water consumption data for hospitals in Wuhan City during the period from 2010 to 2012 were used to verify the effectiveness and practicality of this modified grey GM (0, 1∣sin) model in predicting water consumption. In terms of the model’s fitting performance, the mean absolute percentage error (MAPE) of the modified model was 3.77%, indicating a higher prediction accuracy than the traditional grey GM (0, 1∣sin) model of oscillation sequences. Therefore, the modified grey GM (0, 1∣sin) model we established in this study can provide a scientific reference for administrative departments to forecast water consumption.
机译:缺水是限制城市建设和发展的主要因素之一。科学地预测用水量是合理分配水资源的重要途径。以武汉市医院为例,根据实际用水量的特点,提出了改进的灰色GM(0,1∣sin)振荡序列模型。使用灰色理论,将可变权重增强缓冲算子(VWSBO)引入该模型,以减弱干扰项对数据序列的干扰。利用武汉市2010年至2012年的实际季度总耗水量数据,验证了该改进的灰色GM(0,1∣sin)模型在预测耗水量方面的有效性和实用性。就模型的拟合性能而言,修改后模型的平均绝对百分比误差(MAPE)为3.77%,这表明其预测精度高于传统的灰色GM(0,1∣sin)振荡序列模型。因此,本文建立的改进灰色GM(0,1∣sin)模型可以为行政部门预测用水量提供科学依据。

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