| Autor: |
Guo Kai, Gao Jingsheng, Ye Junneng, Yi Dexin, Kong Song, Huang Hui, Qiu Dan, Gao Wei |
| Jazyk: |
English<br />French |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
MATEC Web of Conferences, Vol 173, p 02021 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2261-236X |
| DOI: |
10.1051/matecconf/201817302021 |
| Popis: |
This paper presented a methodology to assess the operation safety of the urban rail transit system by using the generalized regression neural network. By comparing the evaluated values with the graded scores of the experts, the results indicated that predictions by using the generalized regression neural network only have 5.38% averaged relative error compared with experts’ scores. Therefore, the GRNN was capable of evaluating and predicting the operation safety of the urban rail transit system. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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