Lead zinc ore exploitation process carbon emission short-term prediction method

Abstract

The invention provides a lead zinc ore exploitation process carbon emission short-term prediction method. Grey theories are synthesized to analyze carbon emission sources using motors as research objects and their influence factors in the ore exploitation process. Firstly, the carbon emission sources and their influence factors are analyzed, and the grey theories are adopted to perform clusteringanalysis for like factor merging; secondly, main influence factors are obtained through grey correlation analysis; finally, for solving the super- parameter optimization determining problem, a non-dominated sorting genetic algorithm with an elitist strategy is introduced into a gaussian process regression model, and a gaussian process regression prediction method based on the non-dominated sortinggenetic algorithm with the elitist strategy is proposed. It is proved through an experiment that the proposed prediction method can more accurately predict the carbon emission amount in the lead zincore exploitation process, can be directly achieved on a computer, is good in practicability, low in cost and easy to carry out, and prediction errors are smaller.

Description

technical field [0001] The invention belongs to the technical field of carbon emission forecasting, and in particular relates to a short-term carbon emission forecasting method in the mining process of lead-zinc mines. Background technique [0002] Greenhouse gas emissions from human production activities, especially carbon emissions from fossil fuel combustion, are the main cause of global climate rise. The large amount of carbon produced in industrial production activities makes the problem of carbon emissions particularly prominent. Nowadays, there are endless researches related to carbon emissions, including carbon cost, carbon emissions calculation, and carbon trading market, etc., but there are very few studies on carbon emissions in a specific industrial production process. In fact, the accurate prediction of carbon emissions can rationally use carbon emission equipment, improve economic benefits, save energy and reduce emissions. [0003] As climate issues such as ...

AI Technical Summary

Problems solved by technology

According to research, most of the current carbon emission prediction methods are only applicable to large national-level regions, and most of them are long-term predictions based on ten-year units, so they cannot obtain satisfactory prediction results in the short-term prediction of a production process in a local area , its prediction accuracy did not meet expectations

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