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Attribute reduction method and mental state assessment method on the basis of genetic algorithm and rough set

A technique of genetic algorithm and attribute reduction, which is applied in the field of attribute reduction method based on genetic algorithm and rough set and mental state assessment, and can solve problems such as limited scope of application and inability to obtain attribute reduction results

Active Publication Date: 2015-01-21
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

Therefore, it can be seen that the above-mentioned fitness function has a limited scope of application. For example, when the fitness of chromosome X is large, the correct attribute reduction result cannot be obtained.

Method used

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  • Attribute reduction method and mental state assessment method on the basis of genetic algorithm and rough set
  • Attribute reduction method and mental state assessment method on the basis of genetic algorithm and rough set
  • Attribute reduction method and mental state assessment method on the basis of genetic algorithm and rough set

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Embodiment Construction

[0055] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0056] Such as figure 1 As shown, the mental state assessment method in the present embodiment comprises:

[0057] S1: Take the test items of the training sample as the conditional attribute set, convert the mental state test results of the training sample into the corresponding mental state level according to the mental state evaluation standard, and use all the mental state levels as the decision attribute set, and adopt the rough set principle based on Several training samples construct a decision table, as shown in Table 1 (original data set for mental state assessment), C1 to C37 are test items for mental assessment, D is a decision item (ie test result), and each behavior is a subject The scores of each item, the size of the data set is 334.

[0058] The decision table obtained in this embodiment is the input information system: (U, C...

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Abstract

The invention discloses an attribute reduction method and a mental state assessment method on the basis of a genetic algorithm and a rough set. According to the rough set attribute reduction method on the basis of the genetic algorithm and the rough set, a proper fitness function is set, the application range of the attribute reduction method based on the genetic algorithm and the rough set is widened, and key indicators with concentrated attributes in a decision table can be rapidly and effectively obtained. According to the mental state assessment method, during mental state assessment, the key indicators with the concentrated attributes in the decision table are extracted by the attribute reduction method based on the genetic algorithm and the rough set, and a bayesian network is built and trained according to an extraction result to obtain a classification model for performing mental state assessment. By means of the attribute reduction method and the mental state assessment method on the basis of the genetic algorithm and the rough set, the efficiency of mental state assessment is greatly increased, the accuracy is good, the implementation is easy, and wide adaptability to data can be achieved.

Description

technical field [0001] The invention relates to the technical field of classification prediction, in particular to an attribute reduction method and a mental state evaluation method based on genetic algorithms and rough sets. Background technique [0002] Decision support system is a computer application system that assists decision makers to make decisions through human-computer interaction through data, models and knowledge. In the process of computer-aided decision-making, we often encounter the problem of too many attributes of data, some of which are not important or irrelevant to decision-making. On the one hand, obtaining these attributes will waste manpower and material resources; on the other hand, when these redundant When the amount of residual attribute data is large, it will also affect the efficiency and accuracy of decision-making. In order to improve decision-making efficiency, these redundant attributes can be deleted, and deleting these redundant attribute...

Claims

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Application Information

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IPC IPC(8): G06F19/00G06N3/12
Inventor 段会龙吕旭东尹梓名
Owner ZHEJIANG UNIV
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