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» A new evolutionary method for time series forecasting
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WAIM
2010
Springer
13 years 5 months ago
An Efficient Approach for Mining Segment-Wise Intervention Rules in Time-Series Streams
Huge time-series stream data are collected every day from many areas, and their trends may be impacted by outside events, hence biased from its normal behavior. This phenomenon is ...
Yue Wang, Jie Zuo, Ning Yang, Lei Duan, Hong-Jun L...
EDBT
2010
ACM
184views Database» more  EDBT 2010»
14 years 2 months ago
Aggregation of asynchronous electric power consumption time series knowing the integral
More and more data mining algorithms are applied to a large number of long time series issued by many distributed sensors. The consequence of the huge volume of data is that data ...
Raja Chiky, Laurent Decreusefond, Georges Hé...
JMLR
2008
144views more  JMLR 2008»
13 years 7 months ago
Search for Additive Nonlinear Time Series Causal Models
Pointwise consistent, feasible procedures for estimating contemporaneous linear causal structure from time series data have been developed using multiple conditional independence ...
Tianjiao Chu, Clark Glymour
ICDE
1999
IEEE
209views Database» more  ICDE 1999»
14 years 9 months ago
Efficient Time Series Matching by Wavelets
Time series stored as feature vectors can be indexed by multidimensional index trees like R-Trees for fast retrieval. Due to the dimensionality curse problem, transformations are ...
Kin-pong Chan, Ada Wai-Chee Fu
TMI
2008
136views more  TMI 2008»
13 years 7 months ago
Classification of fMRI Time Series in a Low-Dimensional Subspace With a Spatial Prior
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
François G. Meyer, Xilin Shen