Merkle Merkle tree Based Anomaly Identification Method for Electric Power Marketing Data
When identifying the abnormal data of power marketing,the accuracy of the identification results is low because the original power data itself has certain volatility and irregular development attribute characteristics.Therefore,a Merkle Merkle tree based method for identifying the abnormal data of power marketing is proposed.Firstly,the Merkle Merkle tree is used to preprocess the power marketing data.Based on the data summary in the power marketing data items,a tree structure covering all the power marketing data sets is constructed.In order to reduce repeated operations in the calculation process,the code is embedded in the root node of the Merkle tree to verify that the power marketing data Merkle Merkle tree contains all the data items.In the phase of abnormal data identification,the random decoupling Eigendecomposition of a matrix method is used to decompose the eigenvalues of the Merkle Merkle tree of the power marketing data,and it is used as the criteria for determining Outlier.In the test results,the design method not only showed high stability in identifying different abnormal data classes,but also consistently maintained a low level of overall recognition error.
国家科技期刊平台
NSTL
万方数据
