Machine-learning techniques for geochemical discrimination of 2011 Tohoku tsunami deposits.

ABSTRACT: Geochemical discrimination has recently been recognised as a potentially useful proxy for identifying tsunami deposits in addition to classical proxies such as sedimentological and micropalaeontological evidence. However, difficulties remain because it is unclear which elements best discriminate between tsunami and non-tsunami deposits. Herein, we propose a mathematical methodology for the geochemical discrimination of tsunami deposits using machine-learning techniques. The proposed method can determine the appropriate combinations of elements and the precise discrimination plane that best discerns tsunami deposits from non-tsunami deposits in high-dimensional compositional space through the use of data sets of bulk composition that have been categorised as tsunami or non-tsunami sediments

SUBMITTER: Kuwatani T 

PROVIDER: S-EPMC4233330 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature