Abstract
It is necessary to optimize clustering processing of communication big data numerical attribute feature information in order to improve the ability of numerical attribute mining of communication big data, and thus a big data clustering algorithm based on cloud computing was proposed. The cloud extended distributed feature fitting method was used to process the numerical attribute linear programming of communication big data, and the mutual information feature quantity of communication big data numerical attribute was extracted. Combined with fuzzy C-means clustering and linear regression analysis, the statistical analysis of big data numerical attribute feature information was carried out, and the associated attribute sample set of communication big data numerical attribute cloud grid distribution was constructed. Cloud computing and adaptive quantitative recurrent classifiers were used for data classification, and block template matching and multi-sensor information fusion were combined to search the clustering center automatically to improve the convergence of clustering. The simulation results show that, after the application of this method, the information fusion performance of the clustering process was better, the automatic searching ability of the data clustering center was stronger, the frequency domain equalization control effect was good, the bit error rate was low, the energy consumption was small, and the ability of fuzzy weighted clustering retrieval of numerical attributes of communication big data was effectively improved.
Highlights
With the development of the economy, the progress of science and technology, and the improvement of talent technology, the development of wireless network mobile communication technology has been greatly promoted
A big data clustering algorithm based on cloud computing was proposed
In the clustering space matrix (x1, x2, · · ·, xn ), the basis vector G = [Ek×k |A] of data fuzzy weighted clustering is obtained in order to construct the joint disturbance feature equation group of communication big data numerical attribute feature information clustering
Summary
With the development of the economy, the progress of science and technology, and the improvement of talent technology, the development of wireless network mobile communication technology has been greatly promoted. The multi-dimensional text information clustering processing of communication big data numerical attributes is based onofthe clustering method of the characteristic information of the numerical attribute themulti-dimensional numerical feature extraction rule[4,5,6]. Multi-dimensional processing of communication big multi-dimensional textThe information, as welltext as information realizing ofclustering the multi-dimensional text data classification data numerical attributes is based on the multi-dimensional feature extraction and association rule and recognition. The mutual information features of big data numerical performance of this method in improving the clustering ability of numerical attribute feature information attributes were extracted, and the data classification was carried out by using cloud computing and of communication big data [10,11,12]. The simulation experiments were carried out to show the superior performance of this method in improving the clustering ability of numerical
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