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2022-09-20
Shaomei, Lv, Xiangyan, Zeng, Long, Huang, Lan, Wu, Wei, Jiang.  2021.  Passenger Volume Interval Prediction based on MTIGM (1,1) and BP Neural Network. 2021 33rd Chinese Control and Decision Conference (CCDC). :6013—6018.
The ternary interval number contains more comprehensive information than the exact number, and the prediction of the ternary interval number is more conducive to intelligent decision-making. In order to reduce the overfitting problem of the neural network model, a combination prediction method of the BP neural network and the matrix GM (1, 1) model for the ternary interval number sequence is proposed in the paper, and based on the proposed method to predict the passenger volume. The matrix grey model for the ternary interval number sequence (MTIGM (1, 1)) can stably predict the overall development trend of a time series. Considering the integrity of interval numbers, the BP neural network model is established by combining the lower, middle and upper boundary points of the ternary interval numbers. The combined weights of MTIGM (1, 1) and the BP neural network are determined based on the grey relational degree. The combined method is used to predict the total passenger volume and railway passenger volume of China, and the prediction effect is better than MTIGM (1, 1) and BP neural network.
2019-02-08
Zou, Z., Wang, D., Yang, H., Hou, Y., Yang, Y., Xu, W..  2018.  Research on Risk Assessment Technology of Industrial Control System Based on Attack Graph. 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :2420-2423.

In order to evaluate the network security risks and implement effective defenses in industrial control system, a risk assessment method for industrial control systems based on attack graphs is proposed. Use the concept of network security elements to translate network attacks into network state migration problems and build an industrial control network attack graph model. In view of the current subjective evaluation of expert experience, the atomic attack probability assignment method and the CVSS evaluation system were introduced to evaluate the security status of the industrial control system. Finally, taking the centralized control system of the thermal power plant as the experimental background, the case analysis is performed. The experimental results show that the method can comprehensively analyze the potential safety hazards in the industrial control system and provide basis for the safety management personnel to take effective defense measures.