Recursive information granulation: Aggregation and interpretation issues

被引：45

作者：

Bargiela, A ^{[1
]}

Pedrycz, W

机构：

[1] Nottingham Trent Univ, Dept Comp, Nottingham NG1 4BU, England

[2] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB R3T 2N2, Canada

[3] Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland

来源：

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS | 2003年 / 33卷 / 01期

基金：

加拿大自然科学与工程研究理事会; 英国工程与自然科学研究理事会;

关键词：

complex systems; data mining-oriented time-series analysis; fuzzy sets; granular clustering; information granules and granulation; interval analysis; perception; time-series; traffic data;

D O I：

10.1109/TSMCB.2003.808190

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper contributes to the conceptual and algorithmic framework of information granulation. We revisit the role of information granules that are relevant to several main classes of technical pursuits involving temporal and spatial granulation. A detailed algorithm of information granulation, regarded as an optimization problem reconciling two conflicting design criteria, namely, a specificity of information granules and their experimental relevance (coverage of numeric data), is provided in the paper. The resulting information granules are formalized in the language of set theory (interval analysis). The uniform treatment of data points and data intervals (sets) allows for a recursive application of the algorithm. We assess the quality of information granules through the application of fuzzy c-means (FCM) clustering algorithm. Numerical studies deal with two-dimensional (2-D) synthetic data and experimental traffic data.

引用

页码：96 / 112

页数：17

共 37 条

[1]

[Anonymous], 1999, Fuzzy Cluster Analysis

[2]

BARGIELA A, 2001, GRANULAR COMPUTING

[3]

Berthold M. R., 1999, Intelligent Data Analysis, V3, P37, DOI 10.1016/S1088-467X(99)00004-9

[4]

Bezdek J. C., 1981, Pattern recognition with fuzzy objective function algorithms

[5]

Box G. E. P., 1970, Time series analysis, forecasting and control

[6]

Chiu S, 1996, 1996 BIENNIAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, P461, DOI 10.1109/NAFIPS.1996.534778

[7]

CIOS K, 1998, DATA MINING TECHNIQU

[8]

CLARAMUNT C, 2000, TRANSPORT RES C-EMER, P167

[9]

DAS, 1998, P 4 INT C KNOWL DISC, P16

[10]

DAVIS E, 1987, ARTIF INTELL, V24, P347

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