An evaluation of auto fault diagnosis complexity based on information entropy

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Abstract

The auto fault diagnosis complexity coefficient should be applied for repairing and maintaining price model according to modern auto complex structure. Based on the information entropy theory, this paper proposed the fault diagnosis complexity evaluation for the auto engine fault as a example, five hierarchies structure and evaluate index system were built, then worked out the uniform complexity information entropy value of the auto engine fault diagnosis, which was consistent with the auto repair and maintenance industrial actual situation. The information entropy evaluation provided theoretical basis for the existence and generation of the fault diagnosis complexity coefficient.

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APA

Wang, L., & Zhao, J. (2017). An evaluation of auto fault diagnosis complexity based on information entropy. In Advances in Intelligent Systems and Computing (Vol. 455, pp. 91–101). Springer Verlag. https://doi.org/10.1007/978-3-319-38771-0_9

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