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Prediction of Solar Cycle 24: Using a Connectionist Model of the Emotional System
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES). School of Computer Science, Faculty of Engineering & Physic al Science, The University of Manchester, Manchester, United Kingdom.
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).ORCID-id: 0000-0001-6625-6533
2015 (engelsk)Inngår i: 2015 International Joint Conference on Neural Networks (IJCNN), Piscataway, NJ: IEEE Press, 2015, artikkel-id 7280839Konferansepaper, Publicerat paper (Annet (populærvitenskap, debatt, mm))
Abstract [en]

Accurate prediction of solar activity as one aspect of space weather phenomena is essential to decrease the damage from these activities on the ground based communication, power grids, etc. Recently, the connectionist models of the brain such as neural networks and neuro-fuzzy methods have been proposed to forecast space weather phenomena; however, they have not been able to predict solar activity accurately. That has been a motivation for the development of the connectionist model of the brain; this paper aims to apply a connectionist model of the brain to accurately forecasting solar activity, in particular, solar cycle 24. The neuro-fuzzy method has been referred to as the brain emotional learning-based recurrent fuzzy system (BELRFS). BELRFS is tested for prediction of solar cycle 24, and the obtained results are compared with well-known neuro-fuzzy methods and neural networks as well as with physical-based methods. @2015 IEEE

sted, utgiver, år, opplag, sider
Piscataway, NJ: IEEE Press, 2015. artikkel-id 7280839
Emneord [en]
brain emotional learning-based recurrent fuzzy system, emotional system, solar activity forecasting
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Identifikatorer
URN: urn:nbn:se:hh:diva-29236DOI: 10.1109/IJCNN.2015.7280839ISI: 000370730603137Scopus ID: 2-s2.0-84951103535ISBN: 978-1-4799-1959-8 ISBN: 978-1-4799-1959-15 OAI: oai:DiVA.org:hh-29236DiVA, id: diva2:847120
Konferanse
2015 International Joint Conference on Neural Networks (IJCNN 2015), Killarney, Ireland, July 12–17, 2015
Tilgjengelig fra: 2015-08-19 Laget: 2015-08-19 Sist oppdatert: 2018-03-22bibliografisk kontrollert

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