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Main effect factor analysis method and equipment based on causal model

A causal model and factor analysis technology, applied in the field of safety analysis and calculation, which can solve problems such as incomplete causal analysis methods

Pending Publication Date: 2021-09-14
CHINA ACADEMY OF ELECTRONICS & INFORMATION TECH OF CETC
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Problems solved by technology

[0004] Embodiments of the present invention provide a method and device for analyzing main effect factors based on a causal model to solve the problem of incomplete causal analysis methods based on Bayesian networks in the prior art

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  • Main effect factor analysis method and equipment based on causal model
  • Main effect factor analysis method and equipment based on causal model
  • Main effect factor analysis method and equipment based on causal model

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Embodiment Construction

[0047] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0048] The embodiment of the first aspect of the present invention proposes a method for analyzing main effect factors based on a causal model, such as figure 1 shown, including:

[0049] S1, build a Bayesian network model, and obtain the direct influencing factors of the result nodes.

[0050] It should be noted that the "direct influencing factor" mentioned here can be understood as a node that has a direct causal relationship with the resul...

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Abstract

The invention discloses a main effect factor analysis method and equipment based on a causal model. The main effect factor analysis method based on the causal model comprises the following steps: constructing a Bayesian network model, and obtaining direct influence factors of a result node; obtaining an influence path set of influence of each direct influence factor on a result node; when the influence path set comprises indirect influence paths, analyzing the influence degree of the direct influence factors on the result nodes jointly based on the node interaction effect, and otherwise, calculating the influence degree of the direct influence factors on the result nodes directly by adopting an independent influence degree analysis method; and selecting the direct influence factor corresponding to the maximum value from all the influence degrees as a main effect factor. According to the method, the problem of factor isolation of a single-factor analysis method is solved, the main effect factor is extracted on the basis of fully analyzing the linkage interaction influence between the factors, and the reasonability and credibility of the main effect factor analysis conclusion are improved.

Description

technical field [0001] The invention relates to the field of safety analysis and calculation, in particular to a method and equipment for analyzing main effect factors based on a causal model. Background technique [0002] Causal analysis is an important topic of concern and research in the fields of road traffic accidents, aviation accidents, and risk analysis. It is of great significance for analyzing the causes of accidents, taking effective preventive measures, and reducing the incidence of accidents. As an artificial intelligence technology that combines data mining and uncertainty knowledge reasoning, Bayesian network has been widely used in various fields. Its advantages are mainly reflected in the ability to express the relationship between nodes through directed acyclic graphs. , Uncertain knowledge reasoning through conditional probabilities between nodes. The causal analysis method based on Bayesian network usually includes steps such as factor extraction, constr...

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Application Information

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IPC IPC(8): G06F30/27G06N7/00G06F111/08
CPCG06F30/27G06F2111/08G06N7/01
Inventor 仝小敏吉祥李国栋刘娜洪伟
Owner CHINA ACADEMY OF ELECTRONICS & INFORMATION TECH OF CETC
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