摘要
为实现对近岸海域水环境质量状况的早期预警,构建了近海水环境早期预警模型。首先在布点优化过程中,提出了模糊物元分析法与k-means空间聚类算法相结合的方法,以突出区域监测站位的水环境状态特征,同时兼顾监测站位的空间地理位置等因素;其次,采用突变级数法,以分叉集方程的归一化公式,计算优化监测站位的水环境质量突变状态值,避免了模型中的人为赋值等不确定因素。应用所建模型,选择江苏近海水环境为实例进行预警分析,结果表明,各站位的预警值与水质评价结果一致,验证了模型的合理性。
To achieve early warning of water quality status in coastal ocean, the early warning model of coastal water environment was established. Firstly, the fussy matter-element method combined with k-means clustering algorithm was proposed in the stationing optimization. By this method, the state of wa- ter environment feature in the regional monitoring stations was highlighted, and the space location of the monitoring stations was also considered. Secondly, the catastrophe progression method was adopted. The quality mutation status values of water environment of the optimized monitoring stations were calculated by the normalization assessment of bifurcate equation. Thus, the uncertainty factors such as artificial as- signment can be avoided, and the accuracy of the warning results is improved. Finally, the model was ap- plied to the water environment warning of Jiangsu coastal zone, and the rationality and the feasibility of the model are verified.
出处
《解放军理工大学学报（自然科学版）》
EI
北大核心
2013年第6期653-661,共9页
Journal of PLA University of Science and Technology(Natural Science Edition)
基金
国家科技支撑计划资助项目(2012BAB03B04)
国家自然科学基金资助项目(51179052
50979026
51009048)
江苏908专项基金资助项目(JS-908-02-06)
关键词
近海
水环境
早期预警
布点优化
突变
coastal zone~ water environment
early warning~ stationing optimization
catastrophe
