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
CN113392579APending Publication Date: 2021-09-14CHINA ACADEMY OF ELECTRONICS & INFORMATION TECH OF CETC

Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
CHINA ACADEMY OF ELECTRONICS & INFORMATION TECH OF CETC
Publication Date
2021-09-14

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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.
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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...

Claims

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