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A Brain Emotional Learning-based Prediction Model for the Prediction of Geomagnetic Storms
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). School of Computer Science, Faculty of Engineering & Physical Science, The University of Manchester, Manchester, United Kingdom. (CC-lab)
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). (CC-lab)
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).ORCID iD: 0000-0001-6625-6533
2014 (English)In: Proceedings of the 2014 Federated Conference on Computer Science and Information Systems, Los Alamitos, CA: IEEE Press, 2014, 35-42 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces a new type of brain emotional learning inspired models (BELIMs). The suggested model is  utilized as a suitable model for predicting geomagnetic storms. The model is known as BELPM which is an acronym for Brain Emotional Learning-based Prediction Model. The structure of the suggested model consists of four main parts and mimics the corresponding regions of the neural structure underlying fear conditioning. The functions of these parts are implemented by assigning adaptive networks to the different parts. The learning algorithm of BELPM is based on the steepest descent (SD) and the least square estimator (LSE). In this paper, BELPM is employed to predict geomagnetic storms using the Disturbance Storm Time (Dst) index. To evaluate the performance of BELPM, the obtained results have been compared with the results of the adaptive neuro-fuzzy inference system (ANFIS). © 2014 Polish Information Processing Society.

Place, publisher, year, edition, pages
Los Alamitos, CA: IEEE Press, 2014. 35-42 p.
Series
Annals of Computer Science and Information Systems, ISSN 2300-5963 ; 2
Keyword [en]
Brain Emotional Learning Inspired Models, Disturbance Storm Time (Dst)
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:hh:diva-26711DOI: 10.15439/2014F231ISI: 000358008500005Scopus ID: 2-s2.0-84912092029ISBN: 978-83-60810-58-3 (print)ISBN: 978-83-60810-57-6 (print)ISBN: 978-83-60810-61-3 (print)OAI: oai:DiVA.org:hh-26711DiVA: diva2:754782
Conference
9th International Symposium Advances in Artificial Intelligence and Applications (AAIA'14), Warsaw, Poland, 7-10 September, 2014
Available from: 2014-10-12 Created: 2014-10-12 Last updated: 2017-03-22Bibliographically approved

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Parsapoor, MahboobehBilstrup, UrbanSvensson, Bertil
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Citation style
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