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» A new evolutionary method for time series forecasting
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HIS
2004
13 years 9 months ago
Selection of Time Series Forecasting Models based on Performance Information
In this work, we proposed to use the Zoomed Ranking approach to rank and select time series models. Zoomed Ranking, originally proposed to generate a ranking of candidate algorith...
Patrícia Maforte dos Santos, Teresa Bernard...
FLAIRS
2004
13 years 9 months ago
A Method Based on RBF-DDA Neural Networks for Improving Novelty Detection in Time Series
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...
ESWA
2007
96views more  ESWA 2007»
13 years 7 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...
IJON
2007
106views more  IJON 2007»
13 years 7 months ago
Forecasting the CATS benchmark with the Double Vector Quantization method
The Double Vector Quantization (DVQ) method, a long-term forecasting method based on the self-organizing maps algorithm, has been used to predict the 100 missing values of the CAT...
Geoffroy Simon, John Aldo Lee, Marie Cottrell, Mic...
ICANN
2010
Springer
13 years 8 months ago
A Feature Selection Method for Air Quality Forecasting
Abstract. Local air quality forecasting can be made on the basis of meteorological and air pollution time series. Such data contain redundant information. Partial mutual informatio...
Luca Mesin, Fiammetta Orione, Riccardo Taormina, E...