Results of fitted neural network models on Malaysian aggregate dataset
This result-based paper presents the best results of both fitted BPNN-NAR and BPNN-NARMA on MCCI Aggregate dataset with respect to different error measures. This section discusses on the results in terms of the performance of the fitted forecasting models by each set of input lags and error lags use...
Published in: | Bulletin of Electrical Engineering and Informatics |
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Main Author: | |
Format: | Article |
Language: | English |
Published: |
Institute of Advanced Engineering and Science
2018
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Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049884581&doi=10.11591%2feei.v7i2.1177&partnerID=40&md5=f5523d8b888d2ab3cbbb9ba026e92a92 |
Summary: | This result-based paper presents the best results of both fitted BPNN-NAR and BPNN-NARMA on MCCI Aggregate dataset with respect to different error measures. This section discusses on the results in terms of the performance of the fitted forecasting models by each set of input lags and error lags used, the performance of the fitted forecasting models by the different hidden nodes used, the performance of the fitted forecasting models when combining both inputs and hidden nodes, the consistency of error measures used for the fitted forecasting models, as well as the overall best fitted forecasting models for Malaysian aggregate cost indices dataset. © 2018 Institute of Advanced Engineering and Science. All rights reserved. |
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ISSN: | 20893191 |
DOI: | 10.11591/eei.v7i2.1177 |