Power signal prediction by fuzzy-neural model with considering training problems

Rey Chue Hwang, Huang Chu Huang, Shyh-Jier Huang, Sy Ruen Huang, Yu Ju Chen

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

This paper introduces a new artificial neural network (NN) model, with fuzzy learning algorithm, for power signal prediction. This model is designed to take advantage of the overfitting and underfitting phenomena involved in the training of the neural networks. Results from experimental prediction data of daily power load using the proposed method and the conventional standard error back-propagation (BP) technique are presented in a comparative form. Data from these preliminary experiments shows possible potential for commercial applications.

Original languageEnglish
Pages687-691
Number of pages5
Publication statusPublished - 1996 Dec 1
EventProceedings of the IEEE International Conference on Industrial Technology - Shanghai, China
Duration: 1994 Dec 51994 Dec 9

Other

OtherProceedings of the IEEE International Conference on Industrial Technology
CityShanghai, China
Period94-12-0594-12-09

Fingerprint

Neural networks
Backpropagation
Learning algorithms
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Hwang, R. C., Huang, H. C., Huang, S-J., Huang, S. R., & Chen, Y. J. (1996). Power signal prediction by fuzzy-neural model with considering training problems. 687-691. Paper presented at Proceedings of the IEEE International Conference on Industrial Technology, Shanghai, China, .
Hwang, Rey Chue ; Huang, Huang Chu ; Huang, Shyh-Jier ; Huang, Sy Ruen ; Chen, Yu Ju. / Power signal prediction by fuzzy-neural model with considering training problems. Paper presented at Proceedings of the IEEE International Conference on Industrial Technology, Shanghai, China, .5 p.
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title = "Power signal prediction by fuzzy-neural model with considering training problems",
abstract = "This paper introduces a new artificial neural network (NN) model, with fuzzy learning algorithm, for power signal prediction. This model is designed to take advantage of the overfitting and underfitting phenomena involved in the training of the neural networks. Results from experimental prediction data of daily power load using the proposed method and the conventional standard error back-propagation (BP) technique are presented in a comparative form. Data from these preliminary experiments shows possible potential for commercial applications.",
author = "Hwang, {Rey Chue} and Huang, {Huang Chu} and Shyh-Jier Huang and Huang, {Sy Ruen} and Chen, {Yu Ju}",
year = "1996",
month = "12",
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pages = "687--691",
note = "Proceedings of the IEEE International Conference on Industrial Technology ; Conference date: 05-12-1994 Through 09-12-1994",

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Hwang, RC, Huang, HC, Huang, S-J, Huang, SR & Chen, YJ 1996, 'Power signal prediction by fuzzy-neural model with considering training problems', Paper presented at Proceedings of the IEEE International Conference on Industrial Technology, Shanghai, China, 94-12-05 - 94-12-09 pp. 687-691.

Power signal prediction by fuzzy-neural model with considering training problems. / Hwang, Rey Chue; Huang, Huang Chu; Huang, Shyh-Jier; Huang, Sy Ruen; Chen, Yu Ju.

1996. 687-691 Paper presented at Proceedings of the IEEE International Conference on Industrial Technology, Shanghai, China, .

Research output: Contribution to conferencePaper

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Hwang RC, Huang HC, Huang S-J, Huang SR, Chen YJ. Power signal prediction by fuzzy-neural model with considering training problems. 1996. Paper presented at Proceedings of the IEEE International Conference on Industrial Technology, Shanghai, China, .