Abstract:

This paper select related indexes of ecological tension to establish the RBFN (radial basis function network) model, which is trained and tested according to the research results of ecological tension at different time in different regions. Then, the model is used to evaluate ecological tension of China’s 31 provinces, autonomous regions and municipalities in 2008 and 2013, and the evaluation results visualization expressed with GIS. The results show that the half area is the ecological pressure security status, and Beijing has the largest ecological pressure all the time; 22 provincial administrative regions’ ecological tension are aggravated from 2008 to 2013; regionally, the ecological pressure is the largest in North China, and the smallest in the northwest.

Key words: ecological tension, artificial neural network, RBFN, China

摘要：

为了解决生态压力指数法参数繁多、计算量大、难以进行多区域评价以及因计算过程包含主观因素而导致评价结果偏差等问题, 构建一种简单易行、科学有效的生态压力评价方法。选取生态压力评价相关指标, 建立径向基函数网络(RBFN)模型, 根据目前已有的生态压力指数计算结果, 进行模型训练和检验, 分别对2008年和 2013年中国31个省、自治区和直辖市的生态压力进行评价, 并利用GIS软件, 对评价结果进行可视化表达。结果显示, 中国有一半的地区处于极不安全的生态压力状态, 北京一直是全国生态压力最大的地区; 2008—2013年, 有22个省级行政区的生态压力变大; 生态压力最大的是华北地区, 生态压力最小的是西北地区。

关键词: 生态压力, 人工神经网络, 径向基函数网络, 中国