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Uncertain Temporal Knowledge Reasoning of Train Group Operation Based on Extended Fuzzy-Timing Petri Nets

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Fuzzy Information and Engineering

Part of the book series: Advances in Soft Computing ((AINSC,volume 40))

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Abstract

In order to analyze quantitatively uncertain temporal knowledge in train operation, this paper proposes a temporal knowledge reasoning method, which introduces fuzzy time interval and computation of possibilities to Extended Fuzzy-Timing Petri net(EFTN) in existed train group operation Petri net models. The method can represent the temporal firing uncertainty of each enabled transition, and thus is convenient for modeling in conflict. It also provides a technique for quantitative analysis of possibilities of conflict events. The train group behaviors model shows that the method can deal with temporal uncertainty issues during the train’s movement including multi-path selecting in conflict, train terminal time and the possibility of train operation plan implementation, thus provides the scientific basis for the reasonable train operation plan. Compared with existed methods, this method has some outstanding characteristics such as accurate analysis, simple computation and a wide range of application.

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Bing-Yuan Cao

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Ye, Y., Lu, H., Ma, J., Jia, L. (2007). Uncertain Temporal Knowledge Reasoning of Train Group Operation Based on Extended Fuzzy-Timing Petri Nets. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_7

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  • DOI: https://doi.org/10.1007/978-3-540-71441-5_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71440-8

  • Online ISBN: 978-3-540-71441-5

  • eBook Packages: EngineeringEngineering (R0)

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