Real-time intelligent recommendation method of a simulation model based on incidence relation

FAN Guo-chao; XU Cheng-dong; HU Chun-sheng; SONG Dan

doi:10.13374/j.issn2095-9389.2017.04.019

Volume 39 Issue 4

Apr. 2017

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Article Navigation > Chinese Journal of Engineering > 2017 > 39(4): 626-633

FAN Guo-chao, XU Cheng-dong, HU Chun-sheng, SONG Dan. Real-time intelligent recommendation method of a simulation model based on incidence relation[J]. Chinese Journal of Engineering, 2017, 39(4): 626-633. doi: 10.13374/j.issn2095-9389.2017.04.019

Citation:

FAN Guo-chao, XU Cheng-dong, HU Chun-sheng, SONG Dan. Real-time intelligent recommendation method of a simulation model based on incidence relation[J]. Chinese Journal of Engineering, 2017, 39(4): 626-633. doi: 10.13374/j.issn2095-9389.2017.04.019

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Real-time intelligent recommendation method of a simulation model based on incidence relation

doi: 10.13374/j.issn2095-9389.2017.04.019

1) School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
2) School of Mechanical Engineering, Ningxia University, Yinchuan 750021, China

Received Date: 2016-06-23

Abstract

Abstract

With the availability of a large number of sharing models, model search and task design would be an extremely complex project in the global navigation satellite system (GNSS) -distributed simulation environment (GDSE). For improving the efficiency of model search and task design, a real-time intelligent recommendation method was designed for GDSE. Based on the characteristics of the simulation model, the incidence relation and interface shape of the model were defined in the method and a conditional frequent pattern tree (FP-tree) structure was designed to further improve the retrieval efficiency. The effect of the conditional FP-tree structure was proved theoretically. Then, the calculation method of the model incidence relation degree was proposed and derived based on the Bayesian statistical method. The entire processing of the intelligent recommendation method was designed for implementing it in GDSE. Hence, to check the effect of the real-time intelligent recommendation method, it was implemented in GDSE. Compared with the simulation result of the traditional recommendation method, the model intelligent recommendation method is proved to have a shorter running time and a high accuracy on simulation model recommendation. The computing capability and real-time performance are proved through the simulation. It is demonstrated that the intelligent recommendation method is efficient and flexible for GDSE.
- global navigation satellite system,
- distributed simulation,
- intelligent recommendation,
- incidence relation

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References(17)

References

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