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Bayesian network-based cause scene safety quantitative evaluation method

A Bayesian network and quantitative evaluation technology, which is applied in the field of quantitative evaluation of causal scene safety, can solve problems such as cognitive confusion, and achieve the effect of improving safety, good craftsmanship, and scientific methods

Active Publication Date: 2021-06-18
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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  • Bayesian network-based cause scene safety quantitative evaluation method
  • Bayesian network-based cause scene safety quantitative evaluation method
  • Bayesian network-based cause scene safety quantitative evaluation method

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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 human-computer interaction cognitive overload error model. In the model, the basic value of cognitive resources, the conflict value of cognitive resources and PSF factor are used as input nodes, and the state of cognitive overload 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 consumed by people to complete the task and the resources, while the PSF factor is used as a correction factor to describe the impact of environmental conditions on the state of people. influences. In the output node, we use 7 as the threshold for identifying cognitive overload. Once the calculated cognitive resource consumption exceeds...

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Abstract

The invention provides a Bayesian network-based cause scene safety quantitative evaluation method. The method comprises the following steps of 1, determining cognitive overload model nodes based on a multi-resource theory; 2, determining the correlation of the cognitive overload model based on a multi-resource theory; 3, determining nodes and correlativity of the cognitive confusion model based on a mode matching decision theory; 4, modeling is carried out on the cause scene layer; and 5, modeling is carried out on a human error layer and an accident layer. Through the above steps, the method achieves the purpose of quantitative evaluation of cause scenes under the condition of considering two human error mechanisms of cognitive overload and cognitive confusion, can evaluate the system and equipment in a design stage to support related improvements, and has a very high practical value.

Description

technical field [0001] The present invention provides a method for quantitatively evaluating the safety of causal scenarios based on Bayesian networks. It is based on Bayesian networks and models typical cognitive mechanisms to quantitatively evaluate the possible occurrences of different causal scenarios. Probability of security incidents. The tasks performed by modern equipment are more diverse and the system is more complex, which also determines that the consequences of possible accidents are more serious and the collateral effects are more severe. Therefore, it is necessary to carry out quantitative safety evaluation of possible risk scenarios of 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 occurrence probability, and support the improvement of the relevant design in the design stage, which belongs to the technical field of safety quan...

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Application Information

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