基于多尺度空洞卷积神经网络算法的航空业用电情况分析与预测

Analysis and Forecast of Aviation Power Consumption Based on MSCNN

当前国家将数据纳入第七大生产要素,供电企业如何充分挖掘电力数据资产潜力,对数据要素进行高效配置,成为推动企业数字化发展的关键一环。国网沈阳供电公司依托电力大数据资源优势,基于多尺度空洞卷积神经网络算法,选取沈阳地区航空行业为样本开展用电量分析预测,分析该行业受到外部环境影响程度,从而判断对供电企业的影响,实现对社会经济的“电力数据孪生”。

At present,the state has brought data into the seventh production factor.How to fully tap the potential of power data assets and to allocate data elements efficiently have become a key link in promoting the digital development of enterprises.Relying on the advantages of power big data resources and based on MSCNN(multi-scale hollow convolution neural network)algorithm,State Grid Shenyang Power Supply Company selects the aviation industry in Shenyang as the sample to carry out power consumption analysis and prediction.It analyzes the impact of the industry on the external environment,so as to judge the impact on the power supply enterprises and to realize the“power data twin”of social economy.