摘要
以PSR模型的基本理论为主线,构建了北沟林场人工林生态系统健康状况预警体系。首先利用PSR模型的基本理论,以PSR模型的"压力-状态-响应"为基本框架对森林健康预警指标进行了分类;进而利用RS-粗糙集理论确定森林健康预警指标,建立森林健康预警指标体系;然后利用概率神经网络(PNN)算法对森林健康进行预警;最后针对预警结果提出相应的排警措施。研究结果表明,北沟的森林健康状态整体处于绿色和蓝色警戒内,健康状况良好。
The basic theory of PSR model was taken as main line to construct early warning system for ecosystem health of plantation in Beigou forest farm. Firstly introduced the basic theory of PSR model, and the ＂pressure - state - response＂ from PSR model was taken as the basic framework to classify the early warning indicators of forest health; then using RS-rough set theory to define the RS-warning indicators of forest health in order to establish early warning indicators system of forest health; and then using probabilistic neural network （PNN） algorithm to do early warning for forest health; finally, the corresponding measures of eliminating-warning were put forward according to the early warning results. This study indicated that the overall healthy status of forest in Beigou forest farm is good within green and blue alert.
出处
《湖南农业科学》
2011年第8期165-168,共4页
Hunan Agricultural Sciences
基金
国家林业局林业公益行业科技专项经费项目(200804022)
