Results 251 to 260 of about 40,844,823 (304)

Clustering of time series data—a survey

Pattern Recognition, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Thunshun W Liao
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A review on time series data mining

Engineering Applications of Artificial Intelligence, 2011
Time series is an important class of temporal data objects and it can be easily obtained from scientific and financial applications. A time series is a collection of observations made chronologically. The nature of time series data includes: large in data size, high dimensionality and necessary to update continuously.
Tak-Chung Fu
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On the Collection of Time Series Data

Operational Research Quarterly (1970-1977), 1975
Points concerning the simulation of Box-Jenkins processes and the collection of real series are discussed. These include the effects of rounding, observation error, aggregation of subseries and observing at an incorrect sampling interval; and the time required for a simulated series to "warm up".
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Fuzzy data mining for time-series data

Applied Soft Computing, 2012
Time series analysis has always been an important and interesting research field due to its frequent appearance in different applications. In the past, many approaches based on regression, neural networks and other mathematical models were proposed to analyze the time series.
Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng   +2 more
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Tiered Clustering for Time Series Data

2021
Clustering is an essential unsupervised learning method. While the clustering of discrete data is a reasonably solved problem, sequential data clustering, namely time series data, is still an ongoing problem. Sequential data such as time series is widely used due to its abundance of detailed information.
Ruizhe Ma, Rafal A. Angryk
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Time Series Data

1997
Abstract The entire discussion so far has been conducted assuming that the data are generated independently of each other. While in many situations one can safely believe that dependence is absent or negligible, it can often be the case that the assumption of independence is untenable.
Adrian W Bowman, Adelchi Azzalini
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Data mining in medical time series

Biomedizinische Technik/Biomedical Engineering, 2006
This article proposes a modular, computer-based methodology to describe and compare medical problems using data mining methods. The methodology focuses on a mathematical formulation of typical classification problems, systematic extraction of interpretable features from time series, and an evaluation adapted to problem-specific preferences and ...
Mikut, R., Reischl, M., Burmeister, O., Loose, T.   +3 more
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Real-Time Segmenting Time Series Data

2003
There has been increased interest in time series data mining recently. In some cases, approaches of real-time segmenting time series are necessary in time series similarity search and data mining, and this is the focus of this paper. A real-time iterative algorithm that is based on time series prediction is proposed in this paper.
Aiguo Li, Shengping He, Qin Zheng
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Data Estimation and the Colour of Time Series

Journal of Theoretical Biology, 2001
There has been a long debate on the source of temporal fluctuations in natural population densities. The difficulty is that unpredictable irregularities might be attributed either to external environmental factors or to chaotic dynamics of populations, or even to the interaction of these two factors.
I, Scheuring, O E, Zeöld
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Interactive Exploration of Time Series Data

2001
Widespread interest in discovering features and trends in time- series has generated a need for tools that support interactive exploration. This paper introduces timeboxes: a powerful direct-manipulation metaphor for the specification of queries over time series datasets. Our TimeSearcher implementation of timeboxes supports interactive formulation and
Harry Hochheiser, Ben Shneiderman
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