Stroke detection based on an improved artificial fish swarm algorithm
| Autor: | Ming-Da Zhu, Yi-Zhi Wu, Jun-Bin Li, Sheng Ye |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies Swarm behaviour 020206 networking & telecommunications 02 engineering and technology equipment and supplies medicine.disease Brain simulation Microwave detection Local optimum Microwave imaging Convergence (routing) 0202 electrical engineering electronic engineering information engineering medicine bacteria Fish business Algorithm Stroke ComputingMethodologies_COMPUTERGRAPHICS 021101 geological & geomatics engineering |
| Zdroj: | 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting. |
| Popis: | Stroke detection is to detect brain blood clot based on microwave imaging technology. To solve the stroke detection issue, this paper proposes an improved artificial fish swarm algorithm to overcome the problem of local optima, and to improve the global search ability and convergence speed. By the optimization of artificial fish swarm algorithm and brain simulation model, the stroke location is detected efficiently. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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