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A Quantitative Evaluation Method of Causative Scenario Security Based on Bayesian Network

A Bayesian network and quantitative evaluation technology, applied in the field of quantitative safety evaluation of causal scenarios, can solve problems such as cognitive confusion, and achieve the effect of improving safety, good manufacturability, and broad application value.

Active Publication Date: 2022-07-05
BEIHANG UNIV
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AI Technical Summary

Problems solved by technology

Cognitive confusion occurs when production rules have false pattern matches

Method used

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  • A Quantitative Evaluation Method of Causative Scenario Security Based on Bayesian Network
  • A Quantitative Evaluation Method of Causative Scenario Security Based on Bayesian Network
  • A Quantitative Evaluation Method of Causative Scenario Security Based on Bayesian Network

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Embodiment Construction

[0040] Cognitive Overload Modeling

[0041] The Bayesian network modeling method of cognitive overload describes the generation and evolution process of the cognitive overload mechanism, and combines the Bayesian network to establish a cognitive overload error model for human-computer interaction. In the model, the basic value of cognitive resources, the conflict value of cognitive resources and the PSF factor are used as input nodes, and the cognitive overload state is used as output nodes. In the input node, the basic value of cognitive resources and the conflict value of cognitive resources are used to describe the conflict between the resources and resources consumed by people to complete the task, and the PSF factor is used as a correction factor to describe the effect of environmental conditions on the state of people. influences. In the output node, we take 7 as the threshold for identifying cognitive overload or not. Once the calculated cognitive resource consumption ...

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Abstract

The present invention provides a method for quantitative evaluation of causal scene safety based on a Bayesian network. Correlation; Step 3: Determine the cognitive confusion model node and correlation based on the decision theory of pattern matching; Step 4: Model the causal scene layer; Step 5: Model the human error layer and the accident layer. Through the above steps, the present invention achieves the purpose of quantitatively evaluating the causative scene considering two human error mechanisms of cognitive overload and cognitive confusion. It can evaluate systems and equipment in the design stage to support relevant Improvement, with high practical value.

Description

technical field [0001] The invention provides a Bayesian network-based causal scene security quantitative evaluation method, which is based on the Bayesian network, and is used to quantitatively evaluate the possible occurrence of different causative scenarios by modeling typical cognitive mechanisms. Probability of safety incidents. The tasks performed by modern equipment are more diverse and the system is more complex, which also determines that the possible accident consequences are more serious and the incidental effects are more severe. Therefore, it is necessary to carry out quantitative safety evaluation of the possible risk scenarios of the equipment. The main task of this patent is to apply the Bayesian network to analyze the cause of the accident in the causal scene, determine the evolution path of the accident and its probability of occurrence, so as to support the improvement of the relevant design in the design stage, which belongs to the technical field of quanti...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20
CPCG06F30/20
Inventor 逯鑫曾声奎郭健彬
Owner BEIHANG UNIV