Open AccessA Wavelet Analysis-Based Big Data Spectral Clustering Algorithm for Electric Internet of Things
Author(s) -
Hao Zhang,
Xin Liu,
Donglan Liu,
Hao Yu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1627/1/012007
Subject(s) - cluster analysis , wavelet , spectral clustering , similarity (geometry) , fuzzy clustering , data mining , pattern recognition (psychology) , correlation clustering , cure data clustering algorithm , computer science , artificial intelligence , cascade algorithm , algorithm , mathematics , wavelet transform , wavelet packet decomposition , image (mathematics)
As traditional spectral clustering algorithm is not ideal in big data scenarios, this paper proposes a wavelet analysis-based big data spectral clustering algorithm for Electric Internet of Things. Firstly, using wavelet analysis to measure the dissimilarity of the network communication data, and then the similarity relationship between EIoT data is established to obtain the similarity matrix. Finally the spectral clustering algorithm is used to cluster the data based on similarity matrix obtained above. The experimental results show that the accuracy and purity of the proposed spectral clustering algorithm based on wavelet analysis are respectively 36.2 percent and 19.6 percent higher than traditional algorithms, indicating that the proposed spectral clustering algorithm based on wavelet analysis is effective for EIoT data clustering.