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首页> 外文期刊>Analytica chimica acta >Modeling bio-geochemical interactions in the surface waters of the Gulf of Trieste by three-way principal component analysis (PCA)
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Modeling bio-geochemical interactions in the surface waters of the Gulf of Trieste by three-way principal component analysis (PCA)

机译:通过三向主成分分析(PCA)模拟的里雅斯特湾地表水的生物地球化学相互作用

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摘要

Data of temperature, salinity, dissolved oxygen, nutrients and chlorophyll measured on samples of surface seawater and collected monthly during 2 years in different sites of the Gulf of Trieste are modeled by means of three-way principal component analysis (PCA). Missing values are handled using an expectation maximization algorithm, regression or substitution with random numbers, depending on their origin. Physicochemical parameters are described by three different components that explain the effect of the river input on the seawater pattern, the effect of temperature, and metabolic-catabolic activity of the phytoplankton, respectively. One spatial component accounts for the gradient of influence of the estuarine waters in the Gulf, and three temporal components characterize three main seasonal conditions. Anomalous situations, generated by meteoclimatic events, are highlighted. (C) 1999 Elsevier Science B,V, All rights reserved. [References: 35]
机译:通过三向主成分分析(PCA)对地表海水样品测得的温度,盐度,溶解氧,养分和叶绿素的数据进行测量,并在2年内每月在的里雅斯特湾的不同地点每月收集一次。缺失值使用期望最大化算法处理,根据其来源进行回归或用随机数替代。物理化学参数由三个不同的成分描述,分别解释了河流输入对海水模式的影响,温度的影响以及浮游植物的代谢分解代谢活性。一个空间成分解释了海湾河口水影响的梯度,而三个时间成分则表征了三个主要季节条件。突出显示了由气候变化事件产生的异常情况。 (C)1999 Elsevier Science B,V,保留所有权利。 [参考:35]

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