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» Time Series Prediction by Perturbed Fuzzy Model
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JMLR
2011
187views more  JMLR 2011»
14 years 4 months ago
Robust Statistics for Describing Causality in Multivariate Time Series
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Florin Popescu
CIKM
2011
Springer
13 years 9 months ago
Hybrid models for future event prediction
We present a hybrid method to turn off-the-shelf information retrieval (IR) systems into future event predictors. Given a query, a time series model is trained on the publication...
Giuseppe Amodeo, Roi Blanco, Ulf Brefeld
BMCBI
2007
173views more  BMCBI 2007»
14 years 9 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...
ICASSP
2008
IEEE
15 years 3 months ago
Doppler-variant modeling of the vocal tract
A common technique to deploy linear prediction to nonstationary signals is time segmentation and local analysis. In [1], the temporal changes of linear prediction coefficients (L...
Axel Heim, Uli Sorger, Florian Hug
TFS
2008
157views more  TFS 2008»
14 years 9 months ago
Efficient Self-Evolving Evolutionary Learning for Neurofuzzy Inference Systems
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
Cheng-Jian Lin, Cheng-Hung Chen, Chin-Teng Lin