MODEL SELECTION IN NEURAL NETWORKS BY USING INFERENCE OF F. INCREMENTAL, PCA AND SIC CRITERION FOR TIME SERIES FORCASTING
Abstract. The aim of this paper is to discuss and propose a procedure for model selection in neural network for time series forecasting. We focus on the model selection strategies based on statistical concept, particularly on the inference of R2 incremental, Principal Component Analysis (PCA) of t...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
2006
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Subjects: | |
Online Access: | https://repository.ugm.ac.id/32902/1/1.pdf |