TY  - JOUR
PY  - 2010//
TI  - Two non-probabilistic methods for uncertainty analysis in accident reconstruction
JO  - Forensic science international
A1  - Zou, Tiefang
A1  - Yu, Zhi
A1  - Cai, Ming
A1  - Liu, Juhua
SP  - 134
EP  - 137
VL  - 198
IS  - 1-3
N2  - There are many uncertain factors in traffic accidents, it is necessary to study the influence of these uncertain factors to improve the accuracy and confidence of accident reconstruction results. It is difficult to evaluate the uncertainty of calculation results if the expression of the reconstruction model is implicit and/or the distributions of the independent variables are unknown. Based on interval mathematics, convex models and design of experiment, two non-probabilistic methods were proposed. These two methods are efficient under conditions where existing uncertainty analysis methods can hardly work because the accident reconstruction model is implicit and/or the distributions of independent variables are unknown; and parameter sensitivity can be obtained from them too. An accident case is investigated by the methods proposed in the paper. Results show that the convex models method is the most conservative method, and the solution of interval analysis method is very close to the other methods. These two methods are a beneficial supplement to the existing uncertainty analysis methods.<p />  <p>Language: en</p>
LA  - en
SN  - 0379-0738
UR  - http://dx.doi.org/10.1016/j.forsciint.2010.02.006
ID  - ref1
ER  -