TY - GEN
T1 - Associative model for the forecasting of time series based on the gamma classifier
AU - López-Yáñez, Itzamá
AU - Sheremetov, Leonid
AU - Yáñez-Márquez, Cornelio
PY - 2013
Y1 - 2013
N2 - The paper describes a novel associative model for the forecasting of time series in petroleum engineering. The model is based on the Gamma classifier, which is inspired on the Alpha-Beta associative memories, taking the alpha and beta operators as basis for the gamma operator. The objective is to reproduce and predict future oil production in different scenarios in an adjustable time window. The distinctive features of the experimental data set are spikes, abrupt changes and frequent discontinuities, which considerably decrease the precision of traditional forecasting methods. As experimental results show, this classifier-based predictor exhibits competitive performance. The advantages and limitations of the model, as well as lines of improvement, are discussed.
AB - The paper describes a novel associative model for the forecasting of time series in petroleum engineering. The model is based on the Gamma classifier, which is inspired on the Alpha-Beta associative memories, taking the alpha and beta operators as basis for the gamma operator. The objective is to reproduce and predict future oil production in different scenarios in an adjustable time window. The distinctive features of the experimental data set are spikes, abrupt changes and frequent discontinuities, which considerably decrease the precision of traditional forecasting methods. As experimental results show, this classifier-based predictor exhibits competitive performance. The advantages and limitations of the model, as well as lines of improvement, are discussed.
KW - Gamma classifier
KW - Time series forcasting
KW - associative models
KW - oil production time series
UR - http://www.scopus.com/inward/record.url?scp=84884393137&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-38989-4_31
DO - 10.1007/978-3-642-38989-4_31
M3 - Contribución a la conferencia
SN - 9783642389887
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 304
EP - 313
BT - Pattern Recognition - 5th Mexican Conference, MCPR 2013, Proceedings
T2 - 5th Mexican Conference on Pattern Recognition, MCPR 2013
Y2 - 26 June 2013 through 29 June 2013
ER -