Table 1 Performance of the ANN algorithm.

Performance of classifiers when applied to earthquake and non-earthquake data not used to train the ANN algorithm. In the case of earthquake data, the percentage of records that were correctly classified as earthquakes is shown along with the number of records (in parentheses) for various earthquakes recorded within various distances of the epicenter. For the everyday human activity data, the percentage correctly identified as non-earthquake and falsely identified as earthquakes is shown.

Earthquake classificationWithin 10 kmWithin 20 kmWithin 30 km
1989 Loma Prieta M7100% (2/2)100% (4/4)100% (11/11)
1994 Northridge M6.7100% (4/4)100% (19/19)100% (29/29)
2004 Parkfield M695% (19/20)90% (35/39)86% (36/42)
2014 Napa M6100% (2/2)75% (6/8)42% (10/24)
2014 La Habra M5.1100% (13/13)42% (22/52)25% (30/120)
Human activity classificationNon-earthquake (correct)Earthquake (false)
20150201-2015022893% (3562/3823)7% (261/3823)