Journal
NEUROCOMPUTING
Volume 175, Issue -, Pages 980-989Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2015.06.092
Keywords
Time series forecasting; MLMVN Neural Networks; Oil production
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Funding
- CONACYT-SENER Project [146515]
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In this paper, we discuss the long-term time series forecasting using a Multilayer Neural Network with Multi-Valued Neurons (MLMVN). This is a complex-valued neural network with a derivative-free back-propagation learning algorithm. We evaluate the proposed approach using a real-world data set describing the dynamic behavior of an oilfield asset located in the coastal swamps of the Gulf of Mexico. We show that MLMVN can be efficiently applied to univariate and multivariate one-step- and multi-step ahead prediction of reservoir dynamics. This paper is not only intended for proposing to use a complex-valued neural network for forecasting, but to deeper study some important aspects of the application of ANN models to time series forecasting that could be of the particular interest for pattern recognition community. (C) 2015 Elsevier B.V. All rights reserved.
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