Ecological Security Classification of Regionally Sustainable Utilization of Land Resources Based on SVM

DOI

10.2991/iceesd-18.2018.218How to use a DOI?

Keywords

ecological security; land resource; classification; support vector machine

Abstract

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.

Copyright

© 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/).

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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  - 10.2991/iceesd-18.2018.218
ID  - Zhao2018/05
ER  -