Ecological Security Classification of Regionally Sustainable Utilization of Land Resources Based on SVM
- https://doi.org/10.2991/iceesd-18.2018.218How to use a DOI?
- ecological security; land resource; classification; support vector machine
Ecological security classification of land resources play an important role in sustainable utilization of land resources and improve benefit of healthy development of urbanization in China. According to the county level of ecological security classification of land resources data which is large scale and imbalance, this paper presented a support vector machine (SVM) model to classify the county level of ecological security of land resources. The method was compared with artificial neural network, decision tree, logistic regression, and naive Bayesian classifier regarding the county level of ecological security of land resources classification for Guanzhong urban agglomeration. It is found that the method has the best accuracy rate, hit rate, covering rate and lift coefficient, and provides an effective measurement for county level of ecological security of land resources classification and prediction.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jing Zhao AU - Zhen Jin PY - 2018/05 DA - 2018/05 TI - Ecological Security Classification of Regionally Sustainable Utilization of Land Resources Based on SVM BT - Proceedings of the 2018 7th International Conference on Energy, Environment and Sustainable Development (ICEESD 2018) PB - Atlantis Press SP - 1185 EP - 1189 SN - 2352-5401 UR - https://doi.org/10.2991/iceesd-18.2018.218 DO - https://doi.org/10.2991/iceesd-18.2018.218 ID - Zhao2018/05 ER -