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A neural networks-based evaluation of ecological effectiveness and economic worth in forests

  • Neural Networks
  • Published:
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Abstract

Forests play an essential role in ensuring ecological balance and providing valuable resources. Evaluating their ecological effectiveness and economic value is vital for sustainable forest management. Due to the ecological benefits of the forest ecosystem, China has introduced reforms in its ecological system and incorporated them into its national economic accounting system. This research study selects different types of forests based on their locality and species. It formulates a classifier using Convolution Neural networks (CNN) and Artificial Neural Networks (ANN) data mining techniques. First, this paper briefly discusses data mining methods used to determine the impact of different factors on forest health, quality, and its importance in terrestrial ecology. Second, this research study designs a classifier for labeling forests according to their ecological and economic worth. A confusion matrix was used to ascertain the performance of the classifier. Third, it illustrates an index system for evaluating forest ecosystem service function value and explores dynamic characteristics of forest resource variation and the change process of the forest ecosystem. Finally, a statistical analysis is performed among the proposed study and related studies. The proposed study outperforms its predecessors and depicts that the proposed technique is more accurate than traditional systems. The study showed that the amount of nutrients accumulated by trees and the amount of polluted gas absorbed have doubled, and the growth rate of other functions has also increased by more than 70%. The average growth of forest ecological functions is 97.93%, significantly improving people's awareness of forest resource protection.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This study was funded by the National Natural Science Foundation of China under Grant 71773016.

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Authors and Affiliations

  1. College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, 350002, Fujian, China

    Liulu Zhan & Jianzhou Yang

  2. School of Political and Social Development, Quanzhou Normal University, Quanzhou, 362000, Fujian, China

    Yisheng Liu

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  1. Liulu Zhan
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  2. Jianzhou Yang
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  3. Yisheng Liu
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Correspondence to Jianzhou Yang.

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Zhan, L., Yang, J. & Liu, Y. A neural networks-based evaluation of ecological effectiveness and economic worth in forests. Soft Comput 27, 19339–19358 (2023). https://doi.org/10.1007/s00500-023-09323-1

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