Mining Time Series Data with Two Dimensional Fuzzy Pattern Rules

DOI

10.2991/msam-15.2015.78How to use a DOI?

Keywords

fuzzy pattern rule; referential vector distance; K-means cluster; J-measure;stage characteristics

Abstract

Based on association rules and fuzzy pattern theory, this paper presents a data mining model to extract patterns using two-dimensional fuzzy pattern rules, focusing on the discretization of the time series of dependent and independent variables. The referential vector distance is established as a similarity function, and K-means clustering method is used to acquire the basic trend features. The silhouette coefficient is used to test and analyze the clustering result. Due to the potential delay of the influence of the independent variable on the dependent variable, we determine the optimal lag phase with the sort rule of J-measure based on the principle of maximum entropy. The fuzzy pattern rules of the influence of the independent variable on the dependent variable are determined and interpreted according to the trend features and the fuzzy pattern definitions. The obtained character sets are adjusted and iterated several times based on the definitions of the stage characteristics to locate and interpret the inherent periodic characteristics of the couple of time series. The reliability of the proposed model is tested with an empirical analysis of the effect of the price of corn on that of the pork.More importantly, the analysis unit of this model can be as accurate as the time of a day, suggesting its potential advantages in analyzing the short-term characteristics of time series.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Haifeng Xia
AU  - Bing Chen
AU  - Jiawei Fan
AU  - Zhi Li
AU  - Dan Gao
PY  - 2015/08
DA  - 2015/08
TI  - Mining Time Series Data with Two Dimensional Fuzzy Pattern Rules
BT  - Proceedings of the 2015 International Conference on Modeling, Simulation and Applied Mathematics
PB  - Atlantis Press
SP  - 342
EP  - 349
SN  - 1951-6851
UR  - https://doi.org/10.2991/msam-15.2015.78
DO  - 10.2991/msam-15.2015.78
ID  - Xia2015/08
ER  -