Fitting Analysis and Prediction of Carbon Sequestration in China Based on Clustering and Mode Decomposition
DOI:
https://doi.org/10.54097/hset.v67i.11733Keywords:
Carbon sequestration, Topsis, statistical clustering, pattern decomposition, LSTM.Abstract
The Topsis algorithm is used to evaluate the environmental status of the existing countries and give suggestions for the overall environmental development. In this paper, a method of statistical clustering and pattern decomposition is proposed. Among them, pattern decomposition is an idea to evaluate the work of evaluating carbon sequestration from different angles, and then comprehensively consider the evaluation. Statistical clustering is to describe the similarity between different regions more clearly. This study finally predicts the potential carbon sequestration in China, which is a new attempt for carbon sequestration research. This paper aims to achieve the following objectives : 1. Analyze the common characteristics between different regions in China, and make a reasonable explanation, systematically evaluate the current carbon sequestration level and potential capacity in China.2. 2. Long-term and short-term prediction of China 's future carbon sequestration level. Discuss and clarify the experimental conclusions in detail, and give systematic and reasonable suggestions. It is concluded that the carbon sequestration level of the two regions in the next 40 years will increase by 6 ~ 700,000 tons of carbon sequestration on the basis of the original.
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