An Intelligent Diagnostic System for Evaluating Operator’s Emotions: EEG Processing Toolkit
The article describes a soft computing optimizer of fuzzy controllers. The optimizer is structurally implemented on the basis of three genetic algorithms. From the point of view of the theory of artificial intelligence and fuzzy systems, the soft computing optimizer functions as a universal approxim...
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| Veröffentlicht in: | Biomedical engineering 2020-07, Vol.54 (2), p.145-148 |
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| creator | Ulyanov, S. V. Mamaeva, А. A. Shevchenko, A. V. |
| description | The article describes a soft computing optimizer of fuzzy controllers. The optimizer is structurally implemented on the basis of three genetic algorithms. From the point of view of the theory of artificial intelligence and fuzzy systems, the soft computing optimizer functions as a universal approximator of the training signal operating with the required accuracy; from the point of view of the theory of intelligent management systems, the approximator provides deep machine learning. |
| doi_str_mv | 10.1007/s10527-020-09992-4 |
| format | Article |
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| ispartof | Biomedical engineering, 2020-07, Vol.54 (2), p.145-148 |
| issn | 0006-3398 1573-8256 |
| language | eng |
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| source | Springer Nature - Complete Springer Journals |
| subjects | Algorithms Artificial intelligence Behavior Biomaterials Biomedical Engineering and Bioengineering Diagnostic systems Emotions Engineering Fourier transforms Fuzzy control Fuzzy systems Genetic algorithms Knowledge Machine learning Management systems Neural networks Signal processing Soft computing Software |
| title | An Intelligent Diagnostic System for Evaluating Operator’s Emotions: EEG Processing Toolkit |
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