When North Korea conducted its recent nuclear weapon test, the blast had been detected by a global seismic sensing network operated by the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organisation (CTBTO).

The network, called the International Monitoring System, aims to 'make sure that no nuclear explosion goes undetected'. However, clandestine tests of smaller devices, perhaps by terrorist organisations or other non-state actors, are a different story.

A machine learning system called Vertically Integrated Seismic Analysis (VISA), developed by Erik Sudderth, assistant professor at Brown University in US, helps find those difficult-to-detect events. The International Monitoring System includes 149 certified seismic monitoring stations around the globe.

Those stations send data to the CTBTO's Vienna headquarters, where analysts compile all seismic events into a daily bulletin supplied to nations around the world. Analysts can easily pick out unnatural events from the characteristics of the seismic waveforms they create, but before they can determine whether an event is unnatural, they need to know that an event has occurred.

The older software was making lots of mistakes, Sudderth said. It was wasting analysts' time with false positives. It was also missing lots of smaller events and making errors in triangulating the exact position of events.

The research was published in the journal Bulletin of the Seismological Society of America.

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