Band Segmentation Trick

Band Segmentation and Median

Suppose we have N sensors for an event in 50 Km radius.  We segment all the sensors in five equal bands based on distance from hypocenter. This is shown in the figure below:

Now for each band, we take the sensor with median value of acceleration and its distance from the hypocenter. This central measure is representative of all sensors in that band. We get a total of five values for each event. We find coefficients from training events, and then test using test data set. Thus, for any event, we get total of five estimations, let’s call them mi. As in the case actual richer scale, the ML is the mean of several seismograms; our prediction is also mean of these five readings:

ML= sum ( mi) / 5

We plot these estimated predictions vs. actual magnitudes to see the performance of our algorithm.