Dynamic knowledge updating method based on three decisions in variable-precision rough set model

Abstract

The invention belongs to the technical field of dynamic knowledge updating, and particularly relates to a dynamic knowledge updating method based on three decisions in a variable-precision rough set model, which comprises the following steps: 1, setting a threshold value, and selecting data precision in a rough set; 2, selecting a data relationship in the rough set according to a set precision threshold value, and carrying out data region judgment; 3, generating fuzzy set data in the rough set after judging that the data is finished, and setting an incommitment rule for the fuzzy set data; 4,selecting an approximate space, substituting the generated fuzzy set data into the approximate space, and judging the regional value of the data again; and 5, performing intra-region data comparison on the data generated after judgment, selectively discarding the generated repeated information to obtain updated data, and through three decisions, effectively reducing data updating vulnerabilities caused by two decisions, reducing repeated data of dynamic knowledge updating, and facilitating subsequent updating.

Description

technical field [0001] The invention relates to the technical field of dynamic knowledge updating, in particular to a dynamic knowledge updating method based on three-way decision-making in a variable precision rough set model. Background technique [0002] Three-way decision-making is a decision-making model based on human cognition. It believes that: in the actual decision-making process, people can immediately make quick judgments on things that have sufficient confidence to accept or reject; People tend to delay judging events, that is: delaying decision-making. There are many reasons for delayed decision-making, such as insufficient information, insufficient risk assessment, and insufficient understanding of events. When people's mastery of information, risks, and cognition reaches a certain level, they will make a final judgment of acceptance or rejection. From this perspective, the three-way decision-making is an intermediate step in the final realization of the two-...

AI Technical Summary

Problems solved by technology

[0012] Most of the existing dynamic knowledge update methods in the variable precision rough set model use the update method as a two-branch decision-making method. Based on this method, it is easy to cause the uncertain factors in the rough set to be completely affirmed or denied, and added to the corresponding area. Cause data divergence in subsequent dynamic knowledge updates. According to similar data sets, the factors determined in the rough set model will be similarly processed with the previous uncertain factors, causing knowledge updates to generate fuzzy sets, which will affect subsequent updates.

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