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Methods for fusing uncertain results obtained from different models in accident reconstruction
Considering that almost all existing solutions of fusing different reconstructed results require experts’ opinions and the issue of how to fuse probabilistic results and mixed results has not been discussed. Two solutions are proposed. The first is based on the Monte Carlo Method (FMCM), while the s...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245986/ https://www.ncbi.nlm.nih.gov/pubmed/35784422 http://dx.doi.org/10.1080/20961790.2019.1704474 |
Sumario: | Considering that almost all existing solutions of fusing different reconstructed results require experts’ opinions and the issue of how to fuse probabilistic results and mixed results has not been discussed. Two solutions are proposed. The first is based on the Monte Carlo Method (FMCM), while the second is based on the Sub-Interval Technique (FSIT). The method based on FMCM generates sample points according to the distribution of each uncertain result firstly, and then gives out the cumulative distribution function of the final fused result by statistical analysis. The method based on FSIT gets the result fusion interval set according to lower and upper bounds of all interval results and a given length d of each sub-interval firstly, and then calculate the weighted matrix of the result fusion interval. As a result, the cumulative distribution function of the final fused result can also be given out by statistical analysis. Finally, three real accidents are given to demonstrate the methods of FMCM and FSIT, the results of which show that both work well in practice. |
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