TY - GEN
T1 - Simulated annealing for pattern detection and seismic application
AU - Chen, Kai J.
AU - Huang, Kou-Yuan
PY - 2007/12/1
Y1 - 2007/12/1
N2 - Simulated annealing algorithm is adopted to detect the parameters of lines, circles, ellipses, and hyperbolic patterns. We define the distance from a point to a pattern such that the detection becomes feasible, especially in hyperbola. The proposed simulated annealing parameter detection system has the capability to find a set of parameter vectors with global minimal error to the input data. Using average minimum distance, we propose a method to determine the number of patterns automatically. Experiments on the detection of lines, circles, ellipses, and hyperbolas in images are quite successful. The detection system is also applied to detect the line pattern of direct wave and the hyperbolic pattern of reflection wave in the simulated one-shot seismogram. The results are good and can improve seismic interpretations and further seismic data processing.
AB - Simulated annealing algorithm is adopted to detect the parameters of lines, circles, ellipses, and hyperbolic patterns. We define the distance from a point to a pattern such that the detection becomes feasible, especially in hyperbola. The proposed simulated annealing parameter detection system has the capability to find a set of parameter vectors with global minimal error to the input data. Using average minimum distance, we propose a method to determine the number of patterns automatically. Experiments on the detection of lines, circles, ellipses, and hyperbolas in images are quite successful. The detection system is also applied to detect the line pattern of direct wave and the hyperbolic pattern of reflection wave in the simulated one-shot seismogram. The results are good and can improve seismic interpretations and further seismic data processing.
UR - http://www.scopus.com/inward/record.url?scp=51749089037&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2007.4371003
DO - 10.1109/IJCNN.2007.4371003
M3 - Conference contribution
AN - SCOPUS:51749089037
SN - 142441380X
SN - 9781424413805
T3 - IEEE International Conference on Neural Networks - Conference Proceedings
SP - 477
EP - 482
BT - The 2007 International Joint Conference on Neural Networks, IJCNN 2007 Conference Proceedings
Y2 - 12 August 2007 through 17 August 2007
ER -