Method for realizing d-vine copula soft measurement based on physical information and skewness

By employing the D-Vine Copula soft sensing method based on physical information and skewness, the problem of overfitting in traditional soft sensing methods with small samples is solved, enabling robust prediction and real-time monitoring of complex industrial processes.

CN122196413APending Publication Date: 2026-06-12EAST CHINA UNIV OF SCI & TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
EAST CHINA UNIV OF SCI & TECH
Filing Date
2026-03-10
Publication Date
2026-06-12

AI Technical Summary

Technical Problem

Existing traditional soft sensing methods are difficult to effectively describe the nonlinear, non-Gaussian, and strongly coupled characteristics of industrial processes, and are prone to overfitting with small samples, failing to meet the needs of complex industrial processes for real-time monitoring and refined control.

Method used

We employ the D-Vine Copula soft measurement method based on physical information and skewness. Virtual samples are generated through Latin hypercube sampling, and the binary Copula parameters are optimized using a genetic algorithm. In the prediction stage, the conditional skewness of the test samples is considered, and physical loss and fitness functions are introduced. Mode or mean prediction is selected to improve robustness.

Benefits of technology

It effectively alleviates the overfitting problem under small sample sizes, improves prediction stability and generalization ability, and is suitable for real-time monitoring and control of complex industrial processes.

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Abstract

The present application relates to a kind of method for realizing D-Vine Copula soft measurement based on physical information and skewness, comprising the following steps: obtaining real sample set;Determine the monotonic relationship between output variable and input variable;Virtual sample is obtained using Latin hypercube sampling;Determine the kind of binary Copula;Using genetic algorithm to optimize the parameter of binary Copula, calculate monotonicity loss on virtual sample;The Copula density value of each sampling point is calculated by calculating the input variable of test sample and each sampling point, and the weight of each sampling point is calculated;The conditional skewness of test sample is calculated, and according to the threshold set, majority prediction or mean prediction is selected.The method, system, device, processor and computer readable storage medium thereof for realizing D-Vine Copula soft measurement based on physical information and skewness of the present application are used for the nonlinear, non-Gaussian, variable coupling relationship and small sample problem of industrial data, establish D-Vine Copula soft measurement, consider physical loss using GA to optimize binary Copula parameter, consider test sample conditional skewness, improve prediction stability.
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