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» A new evolutionary method for time series forecasting
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CSDA
2010
111views more  CSDA 2010»
13 years 7 months ago
Robust online signal extraction from multivariate time series
We introduce robust regression-based online filters for multivariate time series and discuss their performance in real time signal extraction settings. We focus on methods that ca...
Vivian Lanius, Ursula Gather
HPCC
2007
Springer
13 years 11 months ago
A New Method for Multi-objective TDMA Scheduling in Wireless Sensor Networks Using Pareto-Based PSO and Fuzzy Comprehensive Judg
In wireless sensor networks with many-to-one transmission mode, a multi-objective TDMA (Time Division Multiple Access) scheduling model is presented, which concerns about the packe...
Tao Wang, Zhiming Wu, Jianlin Mao
ICANNGA
2009
Springer
133views Algorithms» more  ICANNGA 2009»
14 years 2 months ago
Visualizing Time Series State Changes with Prototype Based Clustering
Modern process and condition monitoring systems produce a huge amount of data which is hard to analyze manually. Previous analyzing techniques disregard time information and concen...
Markus Pylvänen, Sami Äyrämö, ...
INFOVIS
1999
IEEE
13 years 12 months ago
Cluster and Calendar Based Visualization of Time Series Data
A new method is presented to get insight into univariate time series data. The problem addressed here is how to identify patterns and trends on multiple time scales (days, weeks, ...
Jarke J. van Wijk, Edward R. van Selow
DCC
2005
IEEE
14 years 7 months ago
The Markov Expert for Finding Episodes in Time Series
We describe a domain-independent, unsupervised algorithm for refined segmentation of time series data into meaningful episodes, focusing on the problem of text segmentation. The V...
Jimming Cheng, Michael Mitzenmacher