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An automatic encoding method for a health diagnosis expert knowledge base

An expert knowledge base and automatic coding technology, applied in the field of automatic coding of health diagnosis expert knowledge base, can solve the problems of time-consuming and cumbersome tests due to the number of tests

Active Publication Date: 2019-04-05
CHENGDU AIRCRAFT INDUSTRY GROUP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there are thousands of items in the knowledge base of health diagnosis experts. Manually writing and testing such a large number of knowledge bases will inevitably consume a lot of time and inevitably make mistakes.
Manually coded schemas can become very cumbersome in scenarios where the knowledge base needs to be modified, and this deficiency is especially pronounced when the expert knowledge base is migrated to a similar system

Method used

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  • An automatic encoding method for a health diagnosis expert knowledge base
  • An automatic encoding method for a health diagnosis expert knowledge base
  • An automatic encoding method for a health diagnosis expert knowledge base

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0041] A method for automatic coding of health diagnosis expert knowledge base, characterized in that it comprises the following steps:

[0042] Step S101: Design a fault attribute information table, the content of the header of the parameter attribute information table is the fault number, the name of the calling function, the input parameter code, the corresponding parameter name, and the fault name;

[0043] Step S102: designing an expert knowledge information table, the content of the header of the expert knowledge information table is the fault node code, fault name, fault criterion, and recovery criterion;

[0044] Step S103: Analyze the logical relationship of the expert knowledge criterion, and design a data structure capable of describing the event criterion according to the internal logical relationship of the event criterion, the data structure supports regularized logic symbols;

[0045] Step S104: Generate a C language code expressing event criterion logic in the ...

Embodiment 2

[0047] A method for automatic coding of health diagnosis expert knowledge base, characterized in that it comprises the following steps:

[0048] Step S101: Design a fault attribute information table, the content of the header of the parameter attribute information table is the fault number, the name of the calling function, the input parameter code, the corresponding parameter name, and the fault name;

[0049] Step S102: designing an expert knowledge information table, the content of the header of the expert knowledge information table is the fault node code, fault name, fault criterion, and recovery criterion;

[0050] Step S103: Analyze the logical relationship of the expert knowledge criterion, and design a data structure capable of describing the event criterion according to the internal logical relationship of the event criterion, the data structure supports regularized logic symbols;

[0051] Step S104: Generate a C language code expressing event criterion logic in the ...

Embodiment 3

[0059] A method for automatic coding of health diagnosis expert knowledge base, characterized in that it comprises the following steps:

[0060] Step S101: Design a fault attribute information table, the content of the header of the parameter attribute information table is the fault number, the name of the calling function, the input parameter code, the corresponding parameter name, and the fault name;

[0061] Step S102: designing an expert knowledge information table, the content of the header of the expert knowledge information table is the fault node code, fault name, fault criterion, and recovery criterion;

[0062] Step S103: Analyze the logical relationship of the expert knowledge criterion, and design a data structure capable of describing the event criterion according to the internal logical relationship of the event criterion, the data structure supports regularized logic symbols;

[0063] Step S104: Generate a C language code expressing event criterion logic in the ...

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Abstract

The invention belongs to the field of artificial intelligence, and particularly relates to an automatic coding method for a health diagnosis expert knowledge base, which is characterized by comprisingthe following steps of: S101, designing a fault attribute information table of which the header content is a fault number, calling a function name, inputting a parameter code, a corresponding parameter name and a fault name; S102, designing an expert knowledge information table, wherein the header content of the expert knowledge information table is a fault node code, a fault name, a fault criterion and a recovery criterion; S103, analyzing a logic relation of expert knowledge criteria, designing a data structure capable of describing the event criteria according to an internal logic relationof the event criteria, and enabling the data structure to support regularized logic symbols; And S104, generating a C language code for expressing the event criterion logic in the form of a state machine according to the C language grammar rule, the special logic symbol expression rule and the analysis result, and calling a compiler for compiling to obtain an executable file.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to an automatic coding method for a health diagnosis expert knowledge base. Background technique [0002] With the development of artificial intelligence technology, expert knowledge base technology has played an important role in the field of health diagnosis. With the continuous enrichment and improvement of expert knowledge, its content and complexity are getting higher and higher. At present, the work of converting the expert knowledge base into C language code that can be recognized by the computer is mainly completed by manual coding. The first step is to analyze the expert knowledge in the expert knowledge base, and analyze the logical relationship among the various parameters. In the second step, expert knowledge is converted into C language code manually. The third step is to conduct a functional test on the encoded expert knowledge base code. At presen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G06F16/36
CPCG16H50/20Y02A90/10
Inventor 谢冬其吕当侠朱明晨
Owner CHENGDU AIRCRAFT INDUSTRY GROUP