To address the problems of multiple influencing factors and low prediction accuracy in the current carbon e-mission prediction of cement enterprises,various prediction models have been constructed with the help of big data ma-chine learning technology.The results show that the prediction accuracy error of the linear regression algorithm model for cement enterprises'carbon emissions is 12.78％,which can be reduced to 9％by machine learning model.However,by im-proving the BP(Back Propagation)network model with intelligent fireworks algorithm,the error can be reduced to only 6％,which can better meet the practical application requirements.Further analysis found that for enterprise carbon emis-sions,"clinker production and net electricity purchase"are the two factors with the most significant impact,while increas-ing the use rate of alternative fuels is currently the main way to achieve energy conservation and emission reduction.
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