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A case-oriented approach for analyzing the uncertainty of a reconstructed result based on the evidence theory

Overview of attention for article published in International Journal of Legal Medicine, July 2018
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Title
A case-oriented approach for analyzing the uncertainty of a reconstructed result based on the evidence theory
Published in
International Journal of Legal Medicine, July 2018
DOI 10.1007/s00414-018-1885-6
Pubmed ID
Authors

Tiefang Zou, Hua Li, Ming Cai, Yuelin Li

Abstract

Uncertainty analysis is an effective methodology to improve the reliability of an accident reconstruction result. Many existing methods can be employed in this field, which can confuse a practicing engineer who does not know these methods well. To make the selection easier, a case-oriented approach was proposed based on the evidence theory. Users only need to input uncertain traces and a selected accident reconstruction model to calculate the uncertainty of reconstructed results using the proposed approach. Three basic steps of the case-oriented approach are as follows: first, all types of input traces should be transformed into their evidence form; then, focal elements of the reconstructed result and their corresponding basic probability assignment (BPA) need to be calculated; finally, the belief function (Bel) and plausibility function (Pl) of the reconstructed results are calculated. Three common conditions, which are accidents with all interval traces, accidents with all probabilistic traces, and accidents with interval and probabilistic traces, were discussed based on the basic steps of the case-oriented approach. Furthermore, methods for how to transform different traces to their evidence form, how to calculate the interval of the response efficiently, and how to fuse high conflict evidence were presented. Numerical cases showed that the approach worked well in all conditions. Finally, a vehicle collisions accident case was presented to demonstrate the application of the proposed approach in practice.

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Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 17%
Researcher 1 17%
Student > Postgraduate 1 17%
Student > Master 1 17%
Unknown 2 33%
Readers by discipline Count As %
Engineering 2 33%
Medicine and Dentistry 1 17%
Materials Science 1 17%
Unknown 2 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 July 2018.
All research outputs
#15,539,088
of 23,094,276 outputs
Outputs from International Journal of Legal Medicine
#978
of 2,091 outputs
Outputs of similar age
#209,136
of 327,553 outputs
Outputs of similar age from International Journal of Legal Medicine
#21
of 55 outputs
Altmetric has tracked 23,094,276 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,091 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 38th percentile – i.e., 38% of its peers scored the same or lower than it.
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We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.