Neuro-fuzzy Models for Geomagnetic Storms Prediction: Using the Auroral Electrojet Index
2014 (English)In: 2014 10th International Conference on Natural Computation (ICNC), Piscataway, NJ: IEEE Press, 2014, 12-17 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2014. 12-17 p.
Adaptive Neuro-fuzzy Inference System, Auroral Electrojet, Brain Emotional Learning-inspired Model, Locally linear model tree learning algorithm
Engineering and Technology
IdentifiersURN: urn:nbn:se:hh:diva-26904DOI: 10.1109/ICNC.2014.6975802ISBN: 978-1-4799-5150-5OAI: oai:DiVA.org:hh-26904DiVA: diva2:759979
11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014), Xiamen, China, 19–21 August, 2014