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Issue title: Fuzzy model for human autonomous computing in extreme surveillance and it’s applications
Guest editors: Varatharajan Ramachandran
Article type: Research Article
Authors: Ma, Xuesonga; b | Chen, Xianghuaa | Geng, Yudea; *
Affiliations: [a] College of Economics and Management, Northeast Forestry University, Harbin, Heilongjiang, China | [b] College of Management, Heilongjiang University of Science and Technology, Harbin, Heilongjiang, China
Correspondence: [*] Corresponding author. Yude Geng, College of Economics and Management, Northeast Forestry University, Harbin, Heilongjiang, China. E-mail: [email protected].
Abstract: In the process of people’s development, many resources in natural resources provide convenience and help for people’s survival and development, and forest is an important part of ecological balanced development. In the process of economic development, forest resources can also bring people a lot of economic benefits. People develop regional forestry economy by planting trees with economic value. Asset assessment of forests can better promote the development of forestry economy and help people better use and manage resources. During the process of forestry economic development, the technology of asset evaluation established on the basis of BP neural network enriches the theoretical content of forestry economic development to a certain extent and provides a more solid theoretical basis for development. At the same time, the qualitative and quantitative methods are combined to ensure that the data are more accurate and the key influencing factors can be better analyzed. Based on the analysis of the relevant research results, this paper takes some trees of the same growth year as the object of study. Using BP neural network to analyze the factors that will change the overall value of forest resources, a special BP neural network model belongs to forestry and economic development is established.
Keywords: Neural network fuzzy model regional forestry economy forest resources assets
DOI: 10.3233/JIFS-189527
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6973-6984, 2021
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