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By comparing the simulated results to congestion forecasts based on real traffic data, we find out which parameter leads to the most realistic result.
However, these data do not contain any specific origin or destination points, so, to calculate actual traffic data, we use a multi-agent approach, presented in "Calculating road usage" section.
To evaluate the added value of the more complete traffic data, we developed a model using traffic data for nationally and provincially managed roads only.
To test the quality and robustness of our road traffic data, we compared our traffic indicators derived from MHD data to comparable indicators using three other data sources.
Using the road traffic data, we used a simplified version of the Nordic prediction method for road traffic noise [see the reports by Lyse Nielsen [ 19] and Jonasson et al [ 23] for a complete description] to estimate noise exposure at the residential locations of the participants.
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Complicating what superficially looks to be a 17-year transition period is the urban traffic survey data we have.
In this section, we use the precipitation and traffic flow data we obtained to calibrate and evaluate our model, and analyze and discuss our simulation results.
Taking these results together, and in conjunction with the in vivo trafficking assay data, we suggest that [BF/S+L/Ep] phytoextract can confer a modulatory effect on cell mobility of mouse BMDCs.
Through intensive simulations based on traffic forecasts extrapolated from French traffic data for 2012, we compute the regulation delays and avoidance maneuvers according to two scenarios: the current regulations and no regulations.
Black Friday, the busiest holiday shopping day in the U.S., is now behind us, and with shopper traffic data streaming in, we can safely say that physical retail is still very much alive.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com