Paper Info
Title
Assessment of error in air quality models using dynamic time warping
Abstract
An estimate of the error between the mean concentration of a released pollutant simulated by an atmospheric dispersion model and the values measured at the ground is obtained using Dynamic Time Warping (DTW). The error measure is relevant to the application with iterative source detection algorithms based on forward numerical transport and dispersion simulations. The new proposed measure is compared with two established error functions commonly used in the literature. A sensitivity study of the error measure to wind direction was performed using real world data from the Prairie Grass field experiment. Whereas both standard measures found smallest error only with a few degrees of wind direction, DTW found the smallest error with a much larger range of wind directions, often as high as 20 degrees.
Year
DOI
Venue
2010
10.1145/1869890.1869895
GIS-DMG
Keywords
Field
DocType
dynamic time warping,error measure,dispersion simulation,atmospheric dispersion model,standard measure,prairie grass field experiment,air quality model,established error function,wind direction,smallest error,new proposed measure,field experiment,atmospheric dispersion,time series analysis
Time series,Dispersion (optics),Dynamic time warping,Simulation,Computer science,Atmospheric dispersion modeling,Algorithm,Wind direction,Air quality index
Conference
Citations 
PageRank 
References 
0
0.34
10
Authors
3
Name
Order
Citations
PageRank
Jessica Lin12306123.11
Guido Cervone24411.29
Pasquale Franzese332.14