基于时间序列模糊分割的通信数据分类算法设计

doi:10.13229/j.cnki.jdxbgxb.20220736

摘要/Abstract

摘要：

为解决通信数据集不平衡性明显导致分类难度大幅上升的问题，提出一种时间序列模糊分割的分类算法。利用主成分分析法取得特征值最大的特征矢量，根据区间数理论建立数据的时间序列，用数据与类别间的兰氏距离测度函数表征通信数据时间序列的分割目标，依据模糊分类矩阵差值与收敛条件的判定关系，获取模糊分割的分类结果。实验结果表明：本文算法3种分类情况的数据数量始终位于相应的理想水平上，正确性较高，错误性与失效性较低。

关键词: 时间序列, 模糊分割, 通信数据, 分类算法, 主成分分析法, 区间模糊数

Abstract:

Due to the obvious unbalance of communication data set， the difficulty of classification is greatly increased. Therefore， a time series fuzzy segmentation classification algorithm is proposed. Using the principal component analysis method， the feature vector with the largest eigenvalue is obtained， the time series of the data is established according to the interval number theory， and the segmentation target of the time series of the communication data is characterized by the Langley distance measure function between the data and the class. The classification result of the fuzzy segmentation is obtained according to the judgment relationship between the difference of the fuzzy classification matrix and the convergence condition. The experimental results verify that the data quantity of the three classification cases is always at the corresponding ideal level， with high accuracy and low error and failure.

Key words: time series, fuzzy segmentation, communication data, classification algorithm, principal component analysis, interval fuzzy number

中图分类号:

TP391

张勇飞,陈涛. 基于时间序列模糊分割的通信数据分类算法设计[J]. 吉林大学学报(工学版), 2023, 53(11): 3268-3273.

Yong-fei ZHANG,Tao CHEN. Design of communication data classification algorithm based on fuzzy segmentation of time series[J]. Journal of Jilin University(Engineering and Technology Edition), 2023, 53(11): 3268-3273.

图/表 3

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参考文献 20

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数据集	正类	负类	总数量
1	1040	124	1164
2	1185	797	1982
3	963	398	1361
4	353	244	597
5	830	212	1042
6	925	341	1266
7	901	180	1081
8	1113	144	1257
9	819	685	1504
10	700	137	837

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