A POD-Based Center Selection for RBF Neural Network in Time Series Prediction Problems
ADAPTIVE AND NATURAL COMPUTING ALGORITHMS, PT 2(2007)
Abstract
Center selection based on proper orthogonal decomposition (POD) is presented to select centers for the radial basis function
(RBF) neural network in prediction of nonlinear time series. The proposed method takes advantages of the time-sequence feature
in time series data and enables the center selection to be implemented in a parallel manner. Simulations on a benchmark problem
and on two predictions of stock prices show that the presented method can be applied effectively to the prediction of nonlinear
time series. Besides possessing higher precisions in training and testing, the proposed method has stronger generalization
and noise resistance abilities, compared to several other popular center selection methods.
MoreTranslated text
Key words
null
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined