灰色模型和岭回归模型在金属矿山深部原岩温度预测中的应用

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中图分类号：TD71 文献标识码：A 文章编号：2097-5465（2026）01-0069-06

Abstract：High-temperaturehazardshavebecomeamajorconstraintonminesafetyandeficientproduction.Torevealthe distributioncharacteristicsofdeeprock temperature，measureddatafromametalminewereanalyzedusinggreypredictionmodeling andridgeregression.Theresultshowastronglinearcorelationbetweenrocktmperatureandburialdepth，withageothemal gradient of about 17 ∘C/km .At the -630m level，rock temperature increases monotonically and nonlinearly with borehole depth， and the roadway thermal influence radius is approximately 18m .Grey model predictions exhibit residuals below 0.63 ，relative errors within 3% ，posterior deviation c valuesbelowO.35，the small-error probability P values equal 1，indicating excellent（Grade I）predictionaccuracyRidgeregressionresultsaligncloselywithmeasuredvaluesacrossalldepths，showingonlyslightdviations inshallwzones.Thisstudyprovidesreliabledatasupportforunderstandingdeprocktemperaturedistributionandmitigatinghightemperature hazards in deep mining environments.

Keywords：rock temperature；greymodel；ridge regression；high-temperature hazard

0 引言

深部资源是我国未来主体能源的后备保障[1-3]。（剩余7373字）