Improved PSR model carbon emission early warning system

The improved PSR model with a biological immune system approach enhances carbon emission prediction and warning by addressing non-linear relationships and adaptability, enabling robust anomaly detection and dynamic analysis for precise carbon emission monitoring.

CN120317482APending Publication Date: 2025-07-15SOUTH CHINA NORMAL UNIV
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Patent Information

Application Number
CN202510268331.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-07
Publication Date
2025-07-15

AI Technical Summary

Technical Problem

Current carbon emission prediction and warning methods struggle with non-linear relationships between carbon emission factors, lack adaptability to policy changes and energy structure shifts, limited ability to detect sudden emission anomalies, and fail to identify underlying issues within the system.

Method used

A carbon emission warning system using an improved PSR model based on biological immune system principles, incorporating data collection, PSR model processing, and biological immune algorithm to dynamically update and adaptively analyze carbon emission data, identifying potential issues and optimal control paths.

Benefits of technology

Enables precise and timely carbon emission prediction and early warning by leveraging the immune algorithm's adaptive learning and anomaly detection capabilities, providing a flexible and efficient method for carbon emission monitoring.

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Abstract

The invention belongs to the field of environmental monitoring and prediction, and particularly relates to an improved PSR (Pressure State Response) model carbon emission early warning system, which is used for carrying out improved PSR model carbon emission early warning based on a biological immune system principle and comprises a data acquisition module, a PSR model, a biological immune algorithm model and an early warning output module, the method is used for identifying abnormal changes of carbon emission and realizing dynamic early warning, and has the advantages of high adaptability, high detection capability, multi-factor comprehensive analysis, identification of potential problems and optimal regulation and control paths existing in the system, and realization of accurate prediction and early warning of carbon emission.
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