標題: Neural network and tree automaton for seismic pattern recognition
作者: Huang, KY
Chao, YH
資訊工程學系
Department of Computer Science
公開日期: 2004
摘要: We combine neural network and syntactic pattern recognition, and propose a tree automaton system for the recognition of structural seismic patterns in a seismogram Multilayer perceptron of the neural network is used for the identification of subpatterns, then a tree representation of the structural seismic pattern is constructed. We use three kinds of modified bottom-up structure preserved error correcting tree automata to recognize the tree representation of syntactic pattern, and propose a new top-down error correcting tree automaton to recognize non-structural preserved seismic pattern. In the experiments, the system is applied to the simulated and the real seismic bright spot patterns. The recognition result can improve seismic interpretation.
URI: http://hdl.handle.net/11536/18206
ISBN: 0-7803-8359-1
ISSN: 1098-7576
期刊: 2004 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS
起始頁: 663
結束頁: 668
Appears in Collections:Conferences Paper