The
data produced from global different branch companies of one enterprise every
day can be regarded as time series data. It is important and valuable for
managers to make planning, decision, and control based on these time series
data (Jing,
H., Junyi,
R., Yanzhi,
D., 2008). Another
important area in data mining centers on the mining of time series and
sequence-based data. Simply put, this involves the mining of a sequence of
data, which can either be referenced by time (time-series, such as stock market
and production process data), or is simply a sequence of data which is ordered
in a sequence. DNA sequence is one of the basic and important data among
biological data. Researching DNA sequence data and then comprehending life
essential is a necessary task in post-genomic era. At present, data mining
technique is one of the most efficient data analysis means, which finds out
information hidden in data. It has also become main data analysis technique
adopted in Bioinformatics. It has been applied in DNA sequence analysis, which
has got wide attention and rapid development. And considerable research
achievements have emerged that provides an overview of research progress in DNA
sequence data mining field(Zhu,
Y.-Y., Xiong,
Y.,2007).  In general, one aspect of mining time series
data focuses on the goal of identifying movements or components which exist
within the data (trend analysis). These can include long-term or trend
movements, seasonal variations, cyclical variations, and random movements (Han
and Kamber, 2001). The analysis and mining of traffic video sequences to
discover important but previously unknown knowledge such as vehicle identification,
traffic flow, queue detection, incident detection, and the spatio-temporal
relations of the vehicles at intersections, provide an economic approach for
daily traffic monitoring operations (Chen,
S.-C., Shyu,
M.-L., Zhang,
C., Strickrott,
J.,2002).