With the increasing number of automation and information technology equipment in power engineering,there are higher requirements for the analysis and processing of power engineering data.In response to this issue,the article conducted research on power engineering data fusion processing technology for multi-source heterogeneity.By performing correlation operations in a pre designed data framework,data monitoring and processing analysis can be achieved.In order to improve the coordination between the overall data and local data,edge adaptive enhancement is applied to the fused data.The power engineering fixed value data processing method is integrated,and the sample data is decomposed into multiple sub datasets.A neural network model is used for classification and fusion,and the Reduce mechanism is used to merge and process the fused data,ultimately outputting results to improve the efficiency of data fusion.The analysis results of a power engineering dataset in a region show that the proposed method is more efficient in processing data,and the absolute error generated is only 1.675%,and it is more suitable for scenarios with large data volume.
维普
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