基于人工神经网络的喀斯特地区水资源承载力综合评价——以贵州省为例

运用BP网络对贵州喀斯特地区水资源承载力进行综合评价,并与灰色关联投影法评价结果进行对比。结果表明,两种方法的评价结果整体差别不大,但安顺市和铜仁地区的承载力差别很大。神经网络法所得结果,铜仁地区水资源开发利用潜力最大,而安顺市则很小,仅高于贵阳市;但灰色关联投影法所得结果,铜仁地区的水资源承载力却比安顺市低很多。通过与前人研究结果比较,BP网络的评价结果更加符合实际情况。应用Kohonen网络进行分析,结果表明水资源总量和经济发展水平是影响贵州各地区水资源承载力的主要因素;此外,人口对遵义市的水资源承载力也有较大的影响,铜仁和毕节地区受喀斯特的影响较其他地区显著。

Comprehensive evaluation on carrying capacity of water resources based on the artificial neural network- A case study in Guizhou Province

This paper uses BP network to evaluate the water resource carrying capacity in karst area and compares the evaluating results with that calculated by gray relational projection method. Evaluating results of the two methods are similar overall. However, the water resource carrying capacity in Anshun and Tongren calculate d by the two ways is quite different. The result of BP network shows that the water resource carrying capacity in Tongren is the greatest, while Anshun is very small, only higher than Guiyang. But the result of gray relational projection shows that the water resource carrying capacity in Tongren is much lower than that in Anshun. To compare with former research results, it is proves that the method of BP network is more reasonable. By means of Kohonen network, the analyzed results show t hat the amount of water resources and economic level is the dominant factors impacting the water resource carrying capacity. In addition, the population has a greater influence to the water resource carrying capacity in Zunyi. The influence of karst conditions to the water resource carrying capacity in Tongren and Bijie is higher than other regions.