摘要
土地资源安全预警是区域资源安全研究的重点,通过构建具有实际操作意义的土地资源安全预警系统,可以进行土地资源安全的综合分析,以此来判断城市土地资源安全变化趋势。以广州市为例,应用人工神经网络改进模型(RBF)进行土地资源安全的综合评价,表明广州市土地资源安全已由轻警转为中警状态。实践证明RBF模型对土地资源安全综合评价具有较高的客观性和准确性。
The land safe pre-waming is the key point of regional resources precaution research. Through constructing an actually operative pre-warning system of land sally, we can analyze and judge the changing tendency of land safety. The hazard degree in Guangzhou was evaluated by the model of Radical Basis Function（RBF）. The results indicate that the degree of land safety has changed from light warning degree to middle warning degree. The practice proves that the RBF is an accurate and objective model in evaluating hazard degree of land safety.
出处
《地理科学》
CSCD
北大核心
2007年第6期774-778,共5页
Scientia Geographica Sinica
基金
国家自然科学基金项目(40771003)
广州市土地利用总体规划修编专题研究论证项目(GMTCO54B009ZFG020JO)资助
