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Development of an indirect method for modelling the water footprint of electricity using wavelet transform coupled with the random forest model

机译:用小波变换与随机林模型建模电力占用水脚印的间接方法

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Hydropower is essential for global electricity production, but it consumes water by evaporation from the reservoir surface. Here, a new approach is introduced in relation to modelling the water footprint of electricity (WFe) from hydropower. Two of the most important variables in calculating the WFe are volume of evaporation (EV) and electricity production (EP). In this study, the random forest (RF) model was used to predict both EV and EP. For analysing hybrid models, wavelet transform was used and wavelet RF (WRF) models were developed. After decomposing the input variables by wavelet transform, the relief algorithm (RA) was used to recognize important components and inserted into the RF model. The proposed approach was applied at Mahabad Hydropower in Iran. The results suggest that applying the wavelet transform on input data and using algorithms such as RA can be regarded as a good approach for modelling of EV and EP.
机译:水电公司对全球电力生产至关重要,但它通过从储层表面蒸发消耗水。这里,关于从水电站建模电力(WFE)的水脚印,引入了一种新方法。计算WFE中最重要的两种变量是蒸发(EV)和电力生产(EP)的体积。在这项研究中,随机森林(RF)模型用于预测EV和EP。为了分析混合模型,使用小波变换并开发了小波RF(WRF)模型。在通过小波变换分解输入变量之后,释放算法(RA)用于识别重要组件并插入RF模型。拟议的方法是在伊朗的Mahabad水电。结果表明,在输入数据上应用小波变换和使用诸如RA的算法可以被视为EV和EP建模的好方法。

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