کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
381010 1437457 2013 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A hybrid intelligent model based on recurrent neural networks and excitable dynamics for price prediction in deregulated electricity market
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A hybrid intelligent model based on recurrent neural networks and excitable dynamics for price prediction in deregulated electricity market
چکیده انگلیسی

This paper examines electricity price time series from dynamical system perspective and proposes a hybrid model which employs a synergistic combination of Recurrent Neural Network (RNN) and coupled excitable system for prediction of future prices in deregulated electricity markets. Driven by profit maximizing decisions taken by various agents, these markets belong to the class of financial systems. However presence of intermittent spikes and complex dynamic nonlinearities in electricity price time series render the prediction task extremely challenging. The approximation ability of Recurrent Neural Networks to map dynamic functions together with sharp jumping attribute of coupled excitable systems allows close approximation of spiky time series. The developed hybrid model was applied for point and interval forecasting in various markets worldwide over different seasons for testing its adaptability in different environments. Satisfactory prediction results were obtained in all the markets, in stable as well as spiking regions of the time series.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 26, Issues 5–6, May–June 2013, Pages 1562–1574
نویسندگان
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