The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Short-term load forecasting using an artificial neural network
Abstract
An artificial neural network (ANN) method is applied to forecast the short-term load for a large power system. The load has two distinct patterns: weekday and weekend-day patterns. The weekend-day pattern includes Saturday, Sunday, and Monday loads. A nonlinear load model is proposed and several structures of an ANN for short-term load forecasting were tested. Inputs to the ANN are past loads and the output of the ANN is the load forecast for a given day. The network with one or two hidden layers was tested with various combinations of neurons, and results are compared in terms of forecasting error. The neural network, when grouped into different load patterns, gives a good load forecast.>
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McClelland, J. L., Rumelhart, D. E., & AU (1987) · doi:10.7551/mitpress/5237.001.0001 · Cited by 3,315
Cited by
Forecasting with artificial neural networks:
Zhang, G., Eddy Patuwo, B., & Y. Hu, M. (1998) · International Journal of Forecasting · doi:10.1016/s0169-2070(97)00044-7 · Cited by 4,229
Short-Term Load Forecasting: Similar Day-Based Wavelet Neural Networks
Chen, Y., Luh, P. B., Guan, C., Zhao, Y., Michel, L. D., Coolbeth, M. A., Friedland, P. B., & Rourke, S. J. (2010) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2030426 · Cited by 444
Metadata
- Authors
- Lee, K. Y., Cha, Y. T., & Park, J. H.
- Venue
- IEEE Transactions on Power Systems
- Published
- 1992
- Volume
- 7
- Issue
- 1
- Pages
- 124-132
- ISSN
- 0885-8950 (ISSN-L)
- OpenAlex
- W2116048577
- Cited by
- 602
- References
- 1
- FWCI
- 21.92
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lee, K. Y., Cha, Y. T., & Park, J. H. (1992). Short-term load forecasting using an artificial neural network. IEEE Transactions on Power Systems. https://doi.org/10.1109/59.141695
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