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Carbon intensity key influence factor identification method based on random forest

A technology that affects factors and carbon intensity, applied in character and pattern recognition, machine learning, computer components, etc., can solve the problems of data dimension limitation, lack of subdivision index control, etc.

Pending Publication Date: 2022-08-09
DALIAN UNIV OF TECH
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Problems solved by technology

However, due to the data dimension limitation of these traditional algorithms, the perspective is often limited to a certain subdivision field (such as energy structure, energy intensity, etc.), lacking the control of subdivision indicators within the category from the perspective of overall social development

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  • Carbon intensity key influence factor identification method based on random forest
  • Carbon intensity key influence factor identification method based on random forest
  • Carbon intensity key influence factor identification method based on random forest

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Embodiment Construction

[0026] The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0027] Liaoning Province is selected as the example area of ​​this embodiment, and the research time range is from 2001 to 2019. The data of carbon intensity and potential impact factors in this region are integrated and processed. The overall process framework is as follows: figure 1 As shown, the algorithm flow is as follows Figure 4 shown, the specific steps are as follows:

[0028] 1) Obtaining data: In the carbon intensity data, carbon emissions are calculated using the estimation method in the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, and the regional gross domestic product (GDP) is derived from the Liaoning Statistical Yearbook. The data of potential carbon intensity impact factors come from the "China Statistical Yearbook", "China Energy Statistical Yearbook", "Liaoning Provincial Statistical Yearbook", "China High-tech In...

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Abstract

The invention relates to the field of carbon emission reduction strategy calculation, in particular to a random forest-based carbon intensity key influence factor identification method. Compared with a traditional carbon strength impact factor analysis method, the method has the advantages that data selection is flexible, and the method is not limited by dimensions, important impact factors in multiple potential impact factors can be accurately recognized, the defect of data dimension limitation of the traditional analysis method is overcome, scientific reference is provided for accurate implementation of a carbon emission reduction scheme, and the method is suitable for popularization and application. And a relative emphasis is provided for formulating a regional carbon emission reduction policy.

Description

technical field [0001] The invention relates to the field of carbon emission reduction strategy calculation, in particular to a method for identifying key influencing factors of carbon intensity based on random forests. Background technique [0002] The issue of climate change has received more and more attention worldwide and is regarded as a challenge that the whole world needs to address in the 21st century. There is a clear link between human emissions and the natural climate system. Among the greenhouse gases, excessive carbon dioxide emissions are the main cause of climate change. By controlling the anthropogenic emissions of carbon dioxide, it is hoped that the trend of temperature rise will be curbed. Carbon intensity is usually used to measure the relationship between the national economic development and carbon emissions of a country (region), and it plays an important role in evaluating the relative emission reduction of developing countries, that is, it represent...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N20/00G06Q50/26
CPCG06N20/00G06Q50/26G06F18/24323Y02P90/84
Inventor 李天鹏郑洪波
Owner DALIAN UNIV OF TECH
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