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Learning based brain emotional intelligence as a new aspect for development of an alarm system

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Abstract

The multi criteria and purposeful prediction approach has been introduced and is implemented by the fast and efficient behavioral based brain emotional learning method. On the other side, the emotional learning from brain model has shown good performance and is characterized by high generalization property. New approach is developed to deal with low computational and memory resources and can be used with the largest available data sets. The scope of paper is to reveal the advantages of emotional learning interpretations of brain as a purposeful forecasting system designed to warning; and to make a fair comparison between the successful neural (MLP) and neurofuzzy (ANFIS) approaches in their best structures and according to prediction accuracy, generalization, and computational complexity. The auroral electrojet (AE) index are used as practical examples of chaotic time series and introduced method used to make predictions and warning of geomagnetic disturbances and geomagnetic storms based on AE index.

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Authors and Affiliations

  1. Unit 20, Floor 5, NO.10, 19th Eastern St., South sarrafha Ave., Darya Building, Saadat Abad, Tehran, Iran

    T. Babaie

  2. Control and Intelligent Processing Center of Excellence, Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran

    T. Babaie & R. Karimizandi

  3. School of Intelligent Systems, Institute for Studies in Theoretical Physics and Mathematics, Tehran, Iran

    C. Lucas

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  1. T. Babaie
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  2. R. Karimizandi
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  3. C. Lucas
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Correspondence to T. Babaie.

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Babaie, T., Karimizandi, R. & Lucas, C. Learning based brain emotional intelligence as a new aspect for development of an alarm system. Soft Comput 12, 857–873 (2008). https://doi.org/10.1007/s00500-007-0258-8

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