谱系聚类法在小区域粮食安全预测中的应用——以昆山市为例

粮食安全对国民经济的可持续发展起着不可替代的基础性作用,小区域由于受政策因素的影响较大,粮食安全相关指标的变化呈一定阶段性,长时间序列的数学规律并不突出,不利于规划工作的展开。论文基于昆山市的研究,提出谱系聚类与数学模型相结合的基本思路,在此基础上推出了聚类结果有效性的量化判定标准并对聚类法运用准则做了深入的探讨。实际数据分析结果表明:昆山的粮食安全相关的社会经济指标变化确实呈明显阶段性;与利用全部时间序列数据建立的模型相比,运用谱系聚类的模型拟合和预测效果都有明显优势;至2015年,昆山市粮食自给率将下降至6%,最小人均耕地面积降低至0.022 hm²。通过进一步的分析、对比及讨论,文章认为,谱系聚类法运用于小区域粮食安全预测,方法可操作性强,结论科学性显著。

The Application of Hierarchical Cluster Analysis to the Prediction of Grain Security of Small Research Areas-A Case Study of Kunshan

Grain security is fundamental to the sustainable development of our society and national economy.As research regions with small area are vulnerable to the impacts of policy changes,indexes related to grain security of these areas often change in the form of stages,which means that the mathematical regularity of long-term datasets is not significant.As a result,it is difficult to implement grain security programming for the future.We put forward a new method of combining hierarchical cluster analysis with tr...