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The Use of Support Vectors from Support Vector Machines for Hydrometeorologic Monitoring Network Analyses
Journal of Hydrology ( IF 6.4 ) Pub Date : 2020-04-01 , DOI: 10.1016/j.jhydrol.2019.124522
W.H. Asquith

Abstract Hydrometeorologic monitoring networks are ubiquitous in contemporary earth-system science. Network stakeholders often inquire about the importance of sites and their locations when discussing funding and monitoring design. Support vector machines (SVMs) can be useful by their assigning each monitoring site as either a support or nonsupport vector. A potentiometric surface was created from synthetic data and 800 random observation locations (sites) as an analog to a groundwater-level network. Using generalized additive models for potentiometric surface prediction, simulations show that a subsample of support vectors from the 800 sites will out perform random samples of sample size equaling the support vector count. Support vector percentages from simulation quantify the recurrence that SVMs assign each site as a support vector, and these percentages in turn measure site importance. An example application of support vector percentages identifies important monitoring sites needed to regionalize the 0.1 annual exceedance probability peak streamflow. The results indicate that 152 of 283 streamgages with support vector percentages equalling 100 percent have not operated since about 2000 and generally have much smaller drainage areas than the greater streamgage network in Texas. The drainage area disparity is an indication of historical imbalance in peak streamflow data acquisition from various stream sizes in Texas.

中文翻译:

来自支持向量机的支持向量在水文气象监测网络分析中的使用

摘要 水文气象监测网络在当代地球系统科学中无处不在。在讨论资金和监控设计时,网络利益相关者经常询问站点及其位置的重要性。支持向量机 (SVM) 可以通过将每个监控站点指定为支持向量或非支持向量来发挥作用。电位表面是根据合成数据和 800 个随机观测位置(站点)创建的,作为地下水位网络的模拟。使用广义加性模型进行电位表面预测,模拟表明来自 800 个站点的支持向量子样本将胜过样本大小等于支持向量计数的随机样本。来自模拟的支持向量百分比量化了 SVM 将每个站点分配为支持向量的重复性,这些百分比反过来衡量网站的重要性。支持向量百分比的示例应用确定了区域化 0.1 年超标概率峰值流量所需的重要监测站点。结果表明,支持向量百分比等于 100% 的 283 个河流中的 152 个自大约 2000 年以来就没有运行,并且通常具有比德克萨斯州更大的河流网络小得多的流域面积。流域差异表明从德克萨斯州不同大小的河流中获取的峰值流量数据的历史不平衡。结果表明,支持向量百分比等于 100% 的 283 个河流中的 152 个自大约 2000 年以来就没有运行,并且通常具有比德克萨斯州更大的河流网络小得多的流域面积。流域差异表明从德克萨斯州不同大小的河流中获取的峰值流量数据的历史不平衡。结果表明,支持向量百分比等于 100% 的 283 个河流中的 152 个自大约 2000 年以来就没有运行,并且通常具有比德克萨斯州更大的河流网络小得多的流域面积。流域差异表明从德克萨斯州不同大小的河流中获取的峰值流量数据的历史不平衡。
更新日期:2020-04-01
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