Hierarchical Culling Algorithm of Unbalanced Big Data under Asynchronous Transmission

doi:10.23940/ijpe.19.12.p24.33123321

Abstract

Abstract: Under asynchronous transmission, the hierarchical distribution of unbalanced big data is large and the recognition ability is not good. In order to improve the hierarchical mining ability of unbalanced big data under asynchronous transmission, it is necessary to carry out unbalanced big data elimination ability. An unbalanced big data hierarchical elimination algorithm based on fuzzy association rules feature extraction is proposed. The storage structure model of unbalanced big data's ternary table under asynchronous transmission is constructed. The cooperative filtering method is used to purify the unbalanced big data and filter the interference components in unbalanced big data under asynchronous transmission, the spatial grid clustering method is used to mine the unbalanced big data classification under asynchronous transmission, and the unbalanced autocorrelation features are extracted. The optimal mining and information fusion of unbalanced big data under asynchronous transmission are realized by the hierarchical distribution detection method, and the hierarchical distribution elimination and data storage optimization of unbalanced big data under asynchronous transmission are realized in the reconstructed phase space. The simulation results show that the correlation matching of unbalanced big data elimination under asynchronous transmission is good, the detection and recognition ability of data are improved, and the data storage structure is optimized. It has good application value in data storage, transmission, and output conversion control.

Key words: asynchronous, transmission, unbalanced big data, hierarchical elimination, mining, storage

Mingyi Duan and Xiaochun Cheng. Hierarchical Culling Algorithm of Unbalanced Big Data under Asynchronous Transmission [J]. Int J Performability Eng, 2019, 15(12): 3312-3321.

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