Data-driven intelligent evaluation model parameter dynamic optimization method, computer device, computer readable storage medium

By using a data-driven intelligent evaluation model dynamic optimization method, the distortion problem caused by the reliance on static parameters in equipment operation evaluation models is solved, achieving adaptive optimization of the model and accuracy of evaluation results, adapting to equipment technology iteration and geological changes.

CN122114710APending Publication Date: 2026-05-29TIANDI CHANGZHOU AUTOMATION +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TIANDI CHANGZHOU AUTOMATION
Filing Date
2026-01-22
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing equipment operation evaluation models rely on static parameters, which leads to distorted evaluation results and cannot adapt to the dynamic changes in equipment technology iteration and data accumulation.

Method used

A data-driven intelligent evaluation model parameter dynamic optimization method is adopted. By acquiring equipment operation data and geological conditions, the evaluation model parameters are dynamically optimized, including constructing an intelligent evaluation model, calculating key indicators and correcting geological conditions, and optimizing the automated operation index of the fully mechanized mining face.

Benefits of technology

The evaluation model has achieved self-learning and self-calibration, ensuring the accuracy and advancement of the evaluation results, reducing manual revision work, and dynamically adapting to changes in equipment and geological conditions.

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Abstract

The application relates to the application of machine learning and data mining in an industrial evaluation system, in particular to a dynamic intelligent evaluation model parameter optimization method based on data driving, which comprises the following steps: obtaining equipment operation data on a working face and calculating key indexes; constructing an intelligent evaluation model based on the key indexes, wherein the intelligent evaluation model outputs an automatic operation index FAI of the fully-mechanized working face; optimizing the intelligent evaluation model based on the key indexes under the basic conditions according to the geological conditions of the working face, and outputting the corrected FAI; and optimizing the corrected FAI based on the man-reducing efficiency, advanced conditions, operation data and the key equipment automatic operation monitoring indexes of the fully-mechanized working face under the corrected basic conditions. According to the application, the internal parameters of the evaluation model can be iteratively optimized adaptively along with the accumulation of actual production data and the progress of the industry technology due to the changes of the equipment operation state and the geological conditions, so that the long-term accuracy and advancement of the model are maintained.
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