2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) 2020
DOI: 10.1109/etfa46521.2020.9212179
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Monte Carlo Simulations for probabilistic validation of consequence reasoning from Multilevel Flow Modelling

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“…Model validation is a common problem in MFM. For example, Nielsen et al [51] proposed a causality validation method that also assumes that rules are invariant, despite making a comparison between causal reasoning in MFM and stochastic causality analysis in order to modify the causal relations used in the function model. Although it remains to be investigated whether new rules exist in the representation of mechanical functions, using new set of rules also increases the difficulty of developing such a rule-based reasoning system because under the unified model basis, it is difficult for a computer to determine which set of rules should be used.…”
mentioning
confidence: 99%
“…Model validation is a common problem in MFM. For example, Nielsen et al [51] proposed a causality validation method that also assumes that rules are invariant, despite making a comparison between causal reasoning in MFM and stochastic causality analysis in order to modify the causal relations used in the function model. Although it remains to be investigated whether new rules exist in the representation of mechanical functions, using new set of rules also increases the difficulty of developing such a rule-based reasoning system because under the unified model basis, it is difficult for a computer to determine which set of rules should be used.…”
mentioning
confidence: 99%