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Situational assessment method based on fuzzy dynamic Bayesian network-adaptive particle filtering

A dynamic Bayesian and particle filtering technology, applied in fuzzy logic-based systems, character and pattern recognition, complex mathematical operations, etc. Improve the speed and real-time performance, overcome incompleteness, and improve the effect of real-time performance

Inactive Publication Date: 2019-07-23
BEIJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0002] The current situation assessment has the following shortcomings: first, the data source is single, incomplete data sources and small changes in data will have a significant impact on the analysis results; second, the situation analysis results obtained from different data sources are single; third, the dynamic situation is wrongly judged, Situation assessment is only performed on information at a single moment, without considering the correlation of information at previous and subsequent moments and the mutual complementarity of information; Fourth, the real-time performance is not high. When the parameter information dimension is too high, the reasoning speed is slow

Method used

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  • Situational assessment method based on fuzzy dynamic Bayesian network-adaptive particle filtering
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  • Situational assessment method based on fuzzy dynamic Bayesian network-adaptive particle filtering

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Embodiment Construction

[0051] Specific implementation plan

[0052] In the following, in conjunction with the attached drawings, take the industrial control network situation assessment as an example. When the safety situation means that the process parameters in the system are within the established safety range of the system, the dangerous situation means that the system is under attack and the process parameters exceed the critical value. The present invention will be explained.

[0053] The first step, data anti-interference and fuzzification processing:

[0054] Extract the data that needs to be processed from the collected data, and use the filling method based on linear regression to establish the missing value variable X i (i = 1, 2,..., m) of the regression model of the filled value variable Y, set m to be 300:

[0055]

[0056] Where a 0 And a 1 Time does not depend on X i The weight parameter.

[0057]

[0058]

[0059] among them, with Are the estimated values ​​of missing value variables and f...

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Abstract

The invention discloses a situational assessment method based on fuzzy dynamic Bayesian network-adaptive particle filtering, and the method comprises the steps of 1, data anti-interference and fuzzification processing, 2, construction of a Bayesian network, 3, establishment of a fuzzy dynamic Bayesian network, 4, segmentation of the fuzzy dynamic Bayesian network, and 5, combination with self-adaptive particle filtering. Compared with a traditional situational assessment method, the method has the advantages that the linear regression model is adopted to fill the data, data fuzzification is achieved by combining attribute deletion and concept tree lifting technologies so as to overcome the incompleteness of the collected data, and the accuracy of the algorithm is improved. Compared with astatic reasoning algorithm, the method has the advantage that the real-time performance of reasoning is improved by intervening time characteristics, and prediction processing is carried out on each group after segmentation of the fuzzy dynamic Bayesian network in combination with self-adaptive particle filtering, so that the rate and the real-time performance of the algorithm are improved.

Description

Technical field [0001] The present invention relates to the field of computer software engineering and situation assessment, specifically, it is mainly a situation assessment method based on fuzzy dynamic Bayesian network-adaptive particle filter. Background technique [0002] The current situation assessment has the following shortcomings: First, the data source is single, incomplete data sources and small changes in data will have a significant impact on the analysis results; second, the situation analysis results obtained from different data sources are single; third, the wrong judgment of the dynamic situation, Situation assessment is only performed on the information at a single moment, without considering the correlation and mutual complementation of the information at the previous and subsequent moments. Fourth, the real-time performance is not high. When the parameter information dimension is too high, the inference speed is slow. Therefore, there is an urgent need for a ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/18G06F17/15G06K9/62G06N7/06
CPCG06F17/18G06F17/15G06N7/06G06F18/24155
Inventor 胡燕祝王英剑艾新波王松
Owner BEIJING UNIV OF POSTS & TELECOMM
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