Neural networks for pattern-based short-term load forecasting: A comparative study
详细信息 查看全文
- 作者：Grzegorz Dudek dudek@el.pcz.czest.pl" class="auth_mail" title="E-mail the corresponding author Author Vitae
- 关键词：Neural networks ; Patterns of seasonal cycles ; Short-term load forecasting ; Time series
- 刊名：Neurocomputing
- 出版年：2016
- 出版时间：12 September 2016
- 年：2016
- 卷：205
- 期：Complete
- 页码：64-74
- 全文大小：3109 K
文摘
- class="listitem" id="list_li0005">
- class="label">•
Neural network models for pattern-based short-term load forecasting are proposed.
- class="label">•
Pattern-based approach simplifies forecasting time series with multiple seasonal cycles.
- class="label">•
MLP, RBFNN, GRNN, fuzzy counterpropagation NN and SOM were compared.
- class="label">•
GRNN and one-neuron perceptron learned locally gave best results in STLF.