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作 者:何世钧[1] 周媛媛[1] 张婷[1] 朱吉光 何培民[2,3] HE Shi-jun;ZHOU Yuan-yuan;ZHANG Ting;ZHU Ji-guang;HE Pei-min(College of information, Shanghai Ocean University, Shanghai 201306, China;College of Fisheries and Life Seiences, Shanghai Ocean University, Shanghai 201306, China;Institutes of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China)
机构地区:[1]上海海洋大学信息学院,上海201306 [2]上海海洋大学水产与生命学院,上海201306 [3]上海海洋大学海洋科学研究院海洋生态环境与修复研究所,上海201306
出 处:《海洋环境科学》2018年第3期326-331,共6页Marine Environmental Science
基 金:国家科技支撑计划项目课题(2012BAC07B03)
摘 要:为寻求基于主导因子的绿潮灾害预测方法,在以2014年南黄海绿潮遥感监测覆盖面积数据的平均增长速率为依据划分阶段的基础上,建立支持向量机(support vector machine,SVM)权重计算模型分析影响绿潮扩散的气候因子的权重变化,给出主导因子的权重交点和在不同阶段的变化规律,使用2015年监测数据验证该方法所得结果,误差为1.8%~7%。结果表明,温度与浪高均值比在形成期小于7,快速增长期为4~6,平稳期为5~7,消亡期大于7,雾霾的平均增长速率差分在形成期大于2或小于-2,快速增长期为-3~2,平稳期为-1~1,消亡期接近0。In order to seek for the green tide disaster’s forecasting method that based on the dominant factor,on the basis of the development stage that relied on the average growth rate of Ulva prolifera green tide remote sensing coverage area data in 2014,analysed weight change of climate factors affecting the expansion of green tide through a support vector machine( SVM) weight calculation model,obtained the dominant factors’ weight intersections and summarized their change regulation in different stages,used the monitoring data in 2015 to verify the result of this method,and the error is 1. 8% ~ 7%. The results showed that mean ratio of temperature and wave height in the early-development phase was below 7,in the rapid growth phase was of 4 to 6,in the stationary phase was of 5 to 7,and in the decline phase was more than 7. The difference of haze’s average growth rate in the early-development phase was more than 2 or less than-2,in the rapid growth phase was of-3 to 2,in the stationary phase was of-1 to 1,and in the decline phase was close to 0.
分 类 号:X55[环境科学与工程—环境工程] X87
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