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Table 4 Summary of performance

From: Detecting activity locations from raw GPS data: a novel kernel-based algorithm

Criteria Aft Comment Akd Comment
Highest proportion of tracks with correctly identified number of stops. depending on parameter value 65.5% Obtained with 1000 m radius 92.3% Obtained with 200 m bandwidth
Number of noise/parameter combinations for which detection correctly identifies three stops for at least 70% of tracks (out of 24 combinations) 3 Performance sharply decreasing with increasing noise; best combination yields 75.6% of correct identification of three-stop tracks 15 10 out of these 15 successfull combinations with correct detection of 90% or more of three-stop tracks
Number of correctly identified stops among tracks with close (<800 m) neighbours 132 Larger radii=better prediction 194 Inversed U-shaped relation to bandwidth: best capacity with ‘average’ bandwidth of 200 m
Number of noise/parameter combinations for which the average number of detected stops is around 3 (2.8<average<3.2) 6 10 noise/parameter combinations for which average=zero 15 2 noise/parameter combinations for which average=zero
Number of noise/parameter combinations for which distance between detected and true stop is less than 15 m in average (out of 24 combinations) 8 Standard-errors larger in AFT than in AKD for all combinations 17 11 combinations with less than 10 m in average
Number of noise/parameter combinations with duration difference between detected and true stop less than 10% error 11 AKD outperforms AFT for 16 out of 24 combinations 16 Duration difference below 5% for 200 m bandwidth at all noise levels
  1. Akd/Aft comparison.