Learning based brain emotional intelligence as a new aspect for development of an alarm system
| Autor: | T. Babaie, R. Karimizandi, Caro Lucas |
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| Rok vydání: | 2007 |
| Předmět: |
Adaptive neuro fuzzy inference system
business.industry Generalization Property (programming) Computer science Emotional intelligence Chaotic Computational intelligence Machine learning computer.software_genre Theoretical Computer Science ALARM Social emotional learning Geometry and Topology Artificial intelligence business computer Software |
| Zdroj: | Soft Computing. 12:857-873 |
| ISSN: | 1433-7479 1432-7643 |
| DOI: | 10.1007/s00500-007-0258-8 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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