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[80760] Artykuł: Implementing Fuzzy Cognitive Maps with neural networks for natural gas predictionCzasopismo: International Conference on Tools with Artificial Intelligence Tom: 30, Strony: 1026-1032ISSN: 1082-3409 ISBN: 978-1-5386-7449-9 Wydawca: IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA Opublikowano: 2018 Seria wydawnicza: Proceedings-International Conference on Tools With Artificial Intelligence Autorzy / Redaktorzy / Twórcy Grupa MNiSW: Konferencja Informatyczna Punkty MNiSW: 70 Klasyfikacja Web of Science: Proceedings Paper Pełny tekst DOI Web of Science Keywords: fuzzy cognitive map  artificial neural network  daily consumption  natural gas prediction   |
The goal of this research study is to test the hardiness of a novel hybrid computational intelligence model in day-ahead natural gas demand prediction. The proposed model combines an evolutionary learned FCM method with a common ANN to construct a cascaded model that leads to high prediction accuracy in most distribution points. The FCM technique is used to provide a model which concepts are used as input nodes in a second-stage ANN model employed to provide the forecast for each gas time series. Learned by structure optimization genetic algorithm, the FCM outputs are fed into an ANN to refine the initial forecast and upgrade the overall forecasting accuracy. The model is applied to five distribution points that compose the natural gas grid of a Greek region, district of Thessaly. This approach enables the comparison of the hybrid model performance on different FCM and ANN structures and on consumption patterns, providing also insights on the characteristics of large urban centers and small towns.