Real-time road transportation safety risk evaluation model based on data-mining

2021 ◽  
Vol 20 (2) ◽  
pp. 168
Author(s):  
Wenhui Luo ◽  
Xingkai Meng ◽  
Fengtian Cai ◽  
Chuna Wu
2013 ◽  
Vol 838-841 ◽  
pp. 1263-1267
Author(s):  
Ke Xu ◽  
Hui Min Li ◽  
Sha Sha Lu

It is inevitable to make the new-built highways under-pass the existing railroad by virtue of high-speed development of the transportation in China. Since the relevant surveys on the safety risk evaluation of this kind of the project are lacked at this current stage as well as the limited referential sample data, the survey is to research the factors of safety risk and the self-characteristics as well as to build up the safety risk evaluation model by means of support vector machine plus the analysis with the help of the project example. It turns out that the analyzed result by means of the model has the propinquity with the expected result, as means the model with the limited samples is characterized of improving the objective correctness of the evaluation result in order to supply a scientific method for the safety evaluation of this kind of projects.


2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Y. P. Jiang ◽  
C. C. Cao ◽  
X. Mei ◽  
H. Guo

These days, in allusion to the traditional network security risk evaluation model, which have certain limitations for real-time, accuracy, characterization. This paper proposed a quantitative risk evaluation model for network security based on body temperature (QREM-BT), which refers to the mechanism of biological immune system and the imbalance of immune system which can result in body temperature changes, firstly, through ther-contiguous bits nonconstant matching rate algorithm to improve the detection quality of detector and reduce missing rate or false detection rate. Then the dynamic evolution process of the detector was described in detail. And the mechanism of increased antibody concentration, which is made up of activating mature detector and cloning memory detector, is mainly used to assess network risk caused by various species of attacks. Based on these reasons, this paper not only established the equation of antibody concentration increase factor but also put forward the antibody concentration quantitative calculation model. Finally, because the mechanism of antibody concentration change is reasonable and effective, which can effectively reflect the network risk, thus body temperature evaluation model was established in this paper. The simulation results showed that, according to body temperature value, the proposed model has more effective, real time to assess network security risk.


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