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http://hdl.handle.net/1942/28510
Title: | Fuzzy Cognitive Maps Employing ARIMA Components for Time Series Forecasting | Authors: | VANHOENSHOVEN, Frank NAPOLES RUIZ, Gonzalo BIELEN, Samantha VANHOOF, Koen |
Issue Date: | 2018 | Publisher: | SPRINGER-VERLAG BERLIN | Source: | Czarnowski, I Howlett, RJ Jain, LC (Ed.). INTELLIGENT DECISION TECHNOLOGIES 2017, KES-IDT 2017, PT I, SPRINGER-VERLAG BERLIN,p. 255-264 | Series/Report: | Smart Innovation Systems and Technologies | Abstract: | In this paper, we address some shortcomings of Fuzzy Cognitive Maps (FCMs) in the context of time series prediction. The transparent and comprehensive nature of FCMs provides several advantages that are appreciated for decision-maker. In spite of this fact, FCMs also have some features that are hard to match with time series prediction, resulting in a prediction power that is probably not as extensive as other techniques can boast. By introducing some ideas from ARIMA models, this paper aims at overcoming some of these concerns. The proposed model is evaluated on a real-world case study, captured in a dataset of crime registrations in the Belgian province of Antwerp. The results have shown that our proposal is capable of predicting multiple steps ahead in an entire system of fluctuating time series. However, these enhancements come at the cost of a lower prediction accuracy and less transparency than standard FCM models can achieve. Therefore, further research is required to provide a comprehensive solution. | Notes: | [Vanhoenshoven, Frank; Napoles, Gonzalo; Bielen, Samantha; Vanhoof, Koen] Hasselt Univ, Fac Business Econ, Agoralaan, B-3590 Diepenbeek, Belgium. | Keywords: | Time Series; Weight Matrix; Forecast Model; Recurrent Neural Network; ARIMA Model | Document URI: | http://hdl.handle.net/1942/28510 | ISBN: | 9783319594200 | DOI: | 10.1007/978-3-319-59421-7_24 | ISI #: | 000432721700024 | Rights: | Springer International Publishing AG 2018 | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2019 |
Appears in Collections: | Research publications |
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