桂林理工大学学报2023，Vol.43Issue(4)：608-616,9.DOI:10.3969/j.issn.1674-9057.2023.04.008
基于SOM神经网络的秦岭北麓保护区域村庄分类与发展策略
Village classification and development strategy in the north foot of Qinling Mountains based on SOM neural network
摘要
Abstract
Protecting the ecological environment of Qinling Mountains is significant to promote ecological civili-zation,maintain ecological security and promote the harmonious coexistence between man and nature.Coordina-ting the conflict between ecological protection and town-village development in the north foot of Qinling Moun-tain is of the top priority in Qinling mountain ecological environment protection in the future.The environmental protection of Qinling Mountains and the construction of towns and villages are planned.A multi-dimensional ru-ral classification and evaluation index system are constructed based on the characteristics of ecological reserves and rural attributes.SOM neural network method is established with index system suitable for the regional envi-ronment.Based on the survey data of 475 villages in the region,the rural types are identified,and the develop-ment strategies for different rural characteristics are implemented.The research shows that the SOM neural net-work classification model can effectively identify the same eigenvalue attributes of other villages,with good rec-ognition accuracy.The model provides support for rural policy formulation and optimization.关键词
秦岭北麓区域/乡村分类/评价指标体系/SOM神经网络算法/发展策略Key words
north foot area of Qinling Mountains/village classification/evaluation index system/SOM neural network algorithm/development strategy分类
土木建筑引用本文复制引用
赵哲,吕楠,姜翠梅..基于SOM神经网络的秦岭北麓保护区域村庄分类与发展策略[J].桂林理工大学学报,2023,43(4):608-616,9.基金项目
陕西省重点领域科技创新团队项目(2020TD-029) （2020TD-029）
