Forest Carbon Sequestration Based on Time Series Analysis and Fuzzy Linear Programming Model

DOI: https://doi.org/10.62517/jmsd.202412203

Author(s)

Cong Gu1,*, Jiayi Xu1, Chenxu Wang2, Shuo Feng3

Affiliation(s)

1School of Mathematics and Informaiton Science, Zhongyuan University of Technology, Zhengzhou, Henan, China 2School of Computer Science, Zhongyuan University of Technology, Zhengzhou, Henan, China 3Software College, Zhongyuan University of Technology, Zhengzhou, Henan, China *Corresponding Author.

Abstract

Forest ecosystems, as the largest carbon sink in terrestrial ecosystems, play an important role in global carbon cycling, climate regulation, and mitigating global warming. To alleviate the problem of the greenhouse effect, the relevant data are collected, then several models are established. Model I: remote sensing carbon sequestration model based on time series. Model II: fuzzy linear programming model based on simulated annealing algorithm. These models are brought into the Amazon forest for universality analysis, and it is estimated that the Amazon forest and forest products will store 17.5-69.3 billion tons of CO₂ within 100 years. As the optimal decision model to design the forest management plan, the models can be bought to different countries, times, and space.

Keywords

Carbon Sequestration; Principal Component Analysis; Time Series Analysis; Simulated Annealing Algorithm; Fuzzy Linear Programming Model

References

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