Abstract
INTRODUCTION SparseNet is a suite of programs designed to produce an automated bulletin of seismic events. It operates on sparse seismic networks or arrays limited to a maximum of eight stations. SparseNet is an application of artificial intelligence techniques to seismic monitoring; a more general survey on AI approaches is given in Joswig (1996). Currently, SparseNet consists of three modules: Sonodet, Coassein, and Coaebull. Sonodet performs pattern recognition on single traces, Coassein evaluates their coincidence by rules, and Coaebull eases comparison with ground truth bulletins, summarized in different performance statistics. The restriction to eight stations was made to avoid the problem of “combinatorial explosion” for our very simple rule-based approach in Coassein, since n events at k stations may cause ( n !) k -1 permutations for phase association. The current results of SparseNet processing are first identifications of seismic events by source region and with magnitude estimates. These approximate event parameters do not...
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