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CAEPIA
2003
Springer
13 years 12 months ago
Time-Series Prediction: Application to the Short-Term Electric Energy Demand
This paper describes a time-series prediction method based on the kNN technique. The proposed methodology is applied to the 24hour load forecasting problem. Also, based on recorded...
Alicia Troncoso Lora, Jesús Riquelme Santos...
CCE
2004
13 years 6 months ago
On the use of reduced order models in bifurcation analysis of distributed parameter systems
Bifurcation theory provides a powerful tool for analyzing the nonlinear dynamic behavior of process systems. However, although the theory in principle applies to lumped as well as...
Yi Liu, Elling W. Jacobsen
ICML
2006
IEEE
14 years 7 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
AUTOMATICA
2008
98views more  AUTOMATICA 2008»
13 years 6 months ago
An algorithm for bounded-error identification of nonlinear systems based on DC functions
This paper presents a guaranteed method for the parameter estimation of nonlinear models in a bounded-error context. This method is based on functions which consists of the differ...
J. M. Bravo, T. Alamo, M. J. Redondo, Eduardo F. C...
AAAI
2007
13 years 9 months ago
Discovering Multivariate Motifs using Subsequence Density Estimation and Greedy Mixture Learning
The problem of locating motifs in real-valued, multivariate time series data involves the discovery of sets of recurring patterns embedded in the time series. Each set is composed...
David Minnen, Charles Lee Isbell Jr., Irfan A. Ess...