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首页> 外文期刊>Proceedings of the International Conference on Coastal Engineering >STATISTICAL PREDICTION OF COASTAL AND ESTUARINE EVOLUTION
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STATISTICAL PREDICTION OF COASTAL AND ESTUARINE EVOLUTION

机译:沿海和河口演变的统计预测

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This paper presents a novel data-driven methodology based on empirical orthogonal teleconnections (EOTs) to analyse and forecast the evolution of coastal navigational channels near the mouth of the Exe estuary, UK. This is the first time EOTs are used in coastal morphodynamics. Therefore, particular emphasis is placed on the comparison of EOTs with the well established empirical orthogonal functions (EOFs) method. EOTs and EOFs are used with a series of 14 surveys, taken approximately every 8 months, covering the period between January 2001 and February 2010. The skill of the methods in producing accurate bathymetric one-step forecasts for February 2010 is analyzed and compared with one-step forecasts based on the raw data. It is found that, provided the order of the autoregressive forecast method is chosen appropriately, EOTs and EOFs are better than the raw data and EOTs outperforms than EOFs. This is attributed to the fact that EOTs, without the orthonormality restriction for the temporal eigenfunctions required in EOFs, capturing the temporal patterns within the data more accurately than EOFs.
机译:本文提出了一种基于经验正交遥连接(EOT)的新型数据驱动方法,以分析和预测英国Exe河口附近海岸航行通道的演变。这是EOT首次用于沿海形态动力学。因此,特别强调将EOT与完善的经验正交函数(EOF)方法进行比较。 EOT和EOF用于大约2001年1月至2010年2月之间的大约每8个月进行的一系列14项调查。分析了产生2010年2月准确的测深单步预报的方法的技巧,并与之进行了比较。基于原始数据的逐步预测。据发现,提供自回归预测方法的顺序被适当地选择,并EOTS的EOF比比的EOF原始数据和EOTS性能优于更好。这归因于这样一个事实,即EOT在没有针对EOF中所需的时间本征函数的正交性限制的情况下,比EOF更加准确地捕获了数据中的时间模式。

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