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 language | English |
|---|---|
| Pages | 687-691 |
| Number of pages | 5 |
| Publication status | Published - 1996 |
| Event | Proceedings of the IEEE International Conference on Industrial Technology - Shanghai, China Duration: 1994 Dec 5 → 1994 Dec 9 |
Other
| Other | Proceedings of the IEEE International Conference on Industrial Technology |
|---|---|
| City | Shanghai, China |
| Period | 94-12-05 → 94-12-09 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
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