Particle Swarm Optimization for Pattern Detection and Seismic Applications
碩士 === 國立交通大學 === 多媒體工程研究所 === 95 === Particle Swarm Optimization (PSO) is adopted to detect parameter pattern (e.g. circle, ellipse, hyperbola and asymptote.) Each particle is represented as parameters of patterns, then swarm of particles search the optimal solution in parameter space. We define ma...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2007
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| Online Access: | http://ndltd.ncl.edu.tw/handle/30834450966114442759 |
| Summary: | 碩士 === 國立交通大學 === 多媒體工程研究所 === 95 === Particle Swarm Optimization (PSO) is adopted to detect parameter pattern (e.g. circle, ellipse, hyperbola and asymptote.) Each particle is represented as parameters of patterns, then swarm of particles search the optimal solution in parameter space. We define mathematical formulas to represent various kinds of parameter patterns, and define the distance from points to patterns. Experiments on simulated image get good detection. The method is also applied to detect the parameters of direct wave (line) and reflected wave pattern (hyperbola) in simulated and real one-shot seismogram, the results can improve seismic interpretation and further seismic data processing.
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