Exploiting the interpretability and forecasting ability of the RBF-AR model for nonlinear time series
Work
Year: 2014
Type: article
Institutions University of Macau, Hefei University of Technology
Cites: 53
Cited by: 46
Related to: 10
FWCI: 0.992
Citation percentile (by year/subfield): 91.46
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: closed