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CSDA
2006
191views more  CSDA 2006»
13 years 8 months ago
Forecasting daily time series using periodic unobserved components time series models
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
Siem Jan Koopman, Marius Ooms
CSSE
2008
IEEE
14 years 2 months ago
Application of New Adaptive Higher Order Neural Networks in Data Mining
This paper introduces an adaptive Higher Order Neural Network (HONN) model and applies it in data mining such as simulating and forecasting government taxation revenues. The propo...
Shuxiang Xu, Ling Chen
INFORMATICALT
2007
71views more  INFORMATICALT 2007»
13 years 7 months ago
Forecast Model of Impact of Meteorological Factors on Coronary Artery Disease Patients
Abstract. A medical-meteorological weather assessment using hybrid spatial classification of synoptic and meteorological data was done. Empirical models for assessment as well as ...
Arvydas Martinkenas, Vytautas Kaminskas, Giedrius ...
FLAIRS
2009
13 years 5 months ago
Multiagent Bayesian Forecasting of Time Series with Graphical Models
Time series are found widely in engineering and science. We study multiagent forecasting in time series, drawing from literature on time series, graphical models, and multiagent s...
Yang Xiang, James Smith, Jeff Kroes
ESWA
2007
96views more  ESWA 2007»
13 years 8 months ago
Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models
Forecasting airborne pollen concentrations is one of the most studied topics in aerobiology, due to its crucial application to allergology. The most used tools for this problem ar...
José Luis Aznarte, José Manuel Benit...