کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
705904 | 1460931 | 2007 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Long-term load forecasting via a hierarchical neural model with time integrators
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
مهندسی انرژی و فناوری های برق
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A novel hierarchical hybrid neural model to the problem of long-term load forecasting is proposed in this paper. The neural model is made up of two self-organizing map nets – one on top of the other –, and a single-layer perceptron. It has application into domains which require time series analysis. The model is compared to a multilayer perceptron. Both the hierarchical and the multilayer perceptron models are trained and assessed on load data extracted from a North-American electric utility. They are required to predict either once every week or once every month the electric peak-load and mean-load during the next two years. The results are presented and evaluated in the paper.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Electric Power Systems Research - Volume 77, Issues 3–4, March 2007, Pages 371–378
Journal: Electric Power Systems Research - Volume 77, Issues 3–4, March 2007, Pages 371–378
نویسندگان
Otávio A.S. Carpinteiro, Rafael C. Leme, Antonio C. Zambroni de Souza, Carlos A.M. Pinheiro, Edmilson M. Moreira,