Neural network algorithm for carbon emission prediction

Abstract

The invention relates to a neural network algorithm for carbon emission prediction in the technical field of environmental protection monitoring. The process comprises the following steps: S1, data acquisition; s2, constructing a neural network algorithm; s3, predicting the carbon emission; s4, classifying and storing; s5, calculating an optimization result; according to different application scenarios of carbon emission and different influence factors, variable coefficients are set, historical data and collected real-time data are combined, and a neural network algorithm for carbon emission prediction is researched, so that the accuracy of carbon emission prediction can be greatly improved, and the carbon emission prediction efficiency is improved. Powerful data support is provided for enterprises or factories in making carbon emission plans, and powerful decision support is provided for total carbon emission control; the variable coefficient is added for coping, a more accurate prediction algorithm is brought to the carbon emission, a more accurate prediction means is provided for enterprises and factories to control the carbon emission, and powerful data support is provided for energy conservation and emission reduction of the enterprises and factories.

Description

technical field [0001] The invention relates to the technical field of environmental protection monitoring, in particular to a neural network algorithm for carbon emission prediction. Background technique [0002] Setting the total carbon emission control target is conducive to coordinating the existing binding indicators such as energy and environment. In particular, it affects the comprehensive transformation of the economic development model and energy structure; the total target can be directly linked to and complement each other with external constraints on sustainable development such as resource carrying capacity and environmental quality; the total carbon constraints can also avoid the use of energy only The potential economic development restrictions brought about by the total constraints leave room for innovation in the development of clean energy. [0003] It can be seen that the total carbon emission is one of the most important tasks in the future. In order to ...

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Problems solved by technology

[0020] There are few existing carbon emission prediction algorithms, and the algorithms of each company are different. At present, most of the prediction algorithms are relatively simple, without considering various changing factors of application scenarios, and the analysis and application of historical data are not detailed enough, so the prediction is not accurate. As a result, there are relatively large deviations in the formulation of follow-up emission reduction plans, and the emission reduction control is not in place. For carbon emissions, in different application scenarios, various influencing factors are different. Variable coefficients are set, combined with historical data, and collected Therefore, it is necessary to study a neural network algorithm for carbon emission prediction

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