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Analysis of Forest Carbon Sequestration Management Plan Based on Neural Network Algorithm

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DOI: 10.23977/agrfem.2022.050101 | Downloads: 4 | Views: 175


Minghao Cui 1, Yuntao Fu 1


1 School of Computer Science and Engineering Northeastern University, Shenyang, Liaoning, China

Corresponding Author

Minghao Cui


In order to predict the future forest carbon sequestration content, local forest managers can make better transition decisions for appropriate forest management plans, so that the trend of forest carbon sequestration content can be stabilized and ecological balance can be better made. In this paper, a linear regression analysis using matlab software was used to estimate the carbon stocks of the United States, Brazil, Indonesia, and the Democratic Republic of Congo for the past 30 years, and then a RBF neural network model was used to predict the forest carbon stocks of the four countries 100 years in the future. This paper applies the model to these four countries to obtain forest management plans suitable for forest development in these four countries, completing the transition between the old and new forest management plans within ten years, and the future forest carbon stocks will remain balanced and stable after the implementation of the plans.


RBF neural network algorithm, Forest Management Plan, Forest carbon stocks


Minghao Cui and Yuntao Fu, Analysis of Forest Carbon Sequestration Management Plan Based on Neural Network Algorithm. Agricultural & Forestry Economics and Management (2022) Vol. 5: 1-6. DOI:


[1] Yanfang Ma, Bing Zhou. Research and application of RBF neural networks. Computer Knowledge and Technology: Academic Edition, 2009, 5(9):7224-7225.
[2] Ying Wu, Dingfang Chen, Xiaobing Tang, etc. A review of neural networks. Science and Technology Progress and Countermeasures, 2002, 19(6): 133-134.
[3] Jinhong Zhang, Jie Song. Short-term prediction of Web service QoS based on RBF neural network. Journal of Liaoning University of Engineering and Technology (Natural Science Edition), 2010, 29(5):918-921.
[4] Food and Agriculture Organization of the United Nations, Global Forest Resources Assessment report, FAO, 2015
[5] Yuzhu Fu, Shaopeng Zhang. Inspiration from foreign forest management experience and research on PPP project model of forest management in China. Forestry Science and Technology, 2020, 45(5):62-66.
[6] Jingfang Gao. Integrated Forest Ecosystem Management: The U.S. Experience and Implications for China. Forestry Economics, 2017(5):40-45.
[7] Dingqiang Sun, Runsheng Yin. Northwest Forestry Program:Experience and Insights from U.S. State Forest Management. Forestry Economics, 2006(2):75-80.
[8] Jizhong Zhou. DRC decides to re-examine forest harvesting contracts. World Forestry News, 2008(32).
[9] Xiangrong Ming. DRC insists on conservation and development of forest resources at the same time. Africa, 2013(1):80-81.
[10] Yi Cheng. Indonesia calls for stronger forest management. International Wood Industry, 2013(1).

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