DocumentCode
1841235
Title
The level of cultivated land security risk in China based on the PNN network
Author
Li, Chunhua ; Li, Ning ; Wang, Nawei ; Levy, Jason
Author_Institution
State Key Lab. of Earth Surface Processes & Resource Ecology, Beijing Normal Univ., Beijing, China
Volume
1
fYear
2011
fDate
13-15 May 2011
Firstpage
373
Lastpage
377
Abstract
Currently, cultivated land areas throughout China are differentially susceptible to a variety of natural hazards, social risks, and economic challenges. A risk evaluation model is developed in order to capture the degree of risk to the quality of cultivated land and cultivated land areas in China. Based on the Probabilistic Neural Network (PNN), the model seeks to provide insights/recommendations on the use of cultivated land in China, by employing a set of environmental indicators. Threshold risk levels are established in order to reduce the vulnerability of cultivated lands. Five cultivated land area risk categories are defined. It is shown that more resources should be dedicated to protecting the environment and cultivated land areas in China. By reducing the risk of natural hazards and socio-economic pressures, it is expected that the quality of cultivated land in China can be improved. Finally, regions primarily dedicated to food production should be given additional protection from natural and anthropogenic risks.
Keywords
hazards; land use planning; neural nets; risk management; socio-economic effects; China; PNN network; cultivated land security risk; economic challenges; environmental indicators; natural hazards; probabilistic neural network; risk evaluation model; social risks; socio-economic pressures; Artificial neural networks; Economics; Neurons; Probabilistic logic; Production; Safety; Training; The security of cultivated land: indicator threshold; risk level: PNN network;
fLanguage
English
Publisher
ieee
Conference_Titel
Business Management and Electronic Information (BMEI), 2011 International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-61284-108-3
Type
conf
DOI
10.1109/ICBMEI.2011.5916951
Filename
5916951
Link To Document