Carbon emission index determination method and device, equipment, storage medium and product

By combining enterprise product production data and external environmental data, and using multiple carbon emission prediction models for weighted fusion and dynamic adjustment of model weights, the problem of inaccurate carbon emission indicator prediction in existing technologies has been solved, achieving more accurate carbon emission indicator prediction.

CN121615853APending Publication Date: 2026-03-06CHINA CONSTRUCTION BANK +1
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Patent Information

Application Number
CN202511750872.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-26
Publication Date
2026-03-06

AI Technical Summary

Technical Problem

In existing technologies, the prediction of corporate carbon emission quotas relies on static historical data or expert assessments, which cannot accurately reflect the actual needs of enterprises, resulting in low accuracy in carbon quota prediction.

Method used

By acquiring enterprise product production data and external environmental data, target features affecting carbon emissions are extracted, and multiple carbon emission prediction models are weighted and fused together. The model weights are dynamically adjusted in combination with industry data and external environmental data to predict carbon emission indicators.

Benefits of technology

This improves the accuracy of carbon emission forecasts, enabling forecasts to more accurately reflect companies' carbon emission needs and enhancing the efficiency of carbon emission management.

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Abstract

The invention discloses a carbon emission index determination method, device and equipment, a storage medium and a product, and is applied to the technical field of carbon quotas, the method comprises the following steps: obtaining product production data and external environment data of a first carbon emission object, the external environment data at least comprising meteorological data; performing feature extraction on the product production data and the external environment data to obtain target features; the target features are input into a plurality of carbon emission prediction models, a carbon emission prediction value output by each carbon emission prediction model is obtained, and the target features have different feature weights in the carbon emission prediction models; determining the model weight of each carbon emission prediction model according to the industry data of the industry to which the first carbon emission object belongs and the external environment data; and performing weighted fusion on the carbon emission prediction values output by the plurality of carbon emission prediction models based on the model weights to obtain a target carbon emission index. Therefore, according to the scheme provided by the invention, the accuracy of carbon emission index prediction can be improved.
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