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Neuro-fuzzy Models for Geomagnetic Storms Prediction : Using the Auroral Electrojet Index
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- Parsapoor, Mahboobeh, 1978- (author)
- Högskolan i Halmstad,Centrum för forskning om inbyggda system (CERES),School of Computer Science, Faculty of Engineering & Physical Science, The University of Manchester, Manchester, United Kingdom
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- Bilstrup, Urban, 1971- (author)
- Högskolan i Halmstad,Centrum för forskning om inbyggda system (CERES)
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- Svensson, Bertil, 1948- (author)
- Högskolan i Halmstad,Centrum för forskning om inbyggda system (CERES)
- (creator_code:org_t)
- Piscataway, NJ : IEEE Press, 2014
- 2014
- English.
- In: 2014 10th International Conference on Natural Computation (ICNC). - Piscataway, NJ : IEEE Press. - 9781479951512 ; , s. 12-17
- Conference paper (peer-reviewed)
Abstract
Subject headings
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- This study presents comparative results obtained from employing four different neuro-fuzzy models to predict geomagnetic storms. Two of these neuro-fuzzy models can be classified as Brain Emotional Learning Inspired Models (BELIMs). These two models are BELFIS (Brain Emotional Learning Based Fuzzy Inference System) and BELRFS (Brain Emotional Learning Recurrent Fuzzy System). The two other models are Adaptive Neuro-Fuzzy Inference System (ANFIS) and Locally Linear Model Tree (LoLiMoT) learning algorithm, two powerful neuro-fuzzy models to accurately predict a nonlinear system. These models are compared for their ability to predict geomagnetic storms using the AE index.
Subject headings
- NATURVETENSKAP -- Fysik (hsv//swe)
- NATURAL SCIENCES -- Physical Sciences (hsv//eng)
- NATURVETENSKAP -- Matematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics (hsv//eng)
Keyword
- Adaptive Neuro-fuzzy Inference System
- Auroral Electrojet
- Brain Emotional Learning-inspired Model
- Locally linear model tree learning algorithm
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- kon (subject category)
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