Trajectories modelling of mesoscale anticyclonic eddies in the Mozambique Channel using ANFIS Fuzzy C-Means

Hanitra Elisa Rasoavololoniaina, Harimino Andriamalala Rajaonarisoa, Roselin Randrianantenaina, A. Ratiarison, Hanitra Elisa, Rasoavololoniaina, Harimino Andriamalala, Rajaonarisoa, Todihasina Roselin, Adolphe Randrianantenaina, Andriamanga
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Abstract

The aim of this paper is to optimize the Fuzzy C-Means (FCM) model of the ANFIS neuro-fuzzy system to model the four types of mesoscale anticyclonic eddy trajectories in the Mozambique Channel as a function of the variables eddy speed average of contour, amplitude and diameter, horizontal wind, atmospheric pressure and bathymetry. The study area concerns the eastern part of the Mozambique Channel between longitudes 41°E-44°E and latitudes 16°S-25°S. We classified the eddy trajectories of interest in our study area into four types according to their formation and dissipation zones. The data used are from the mesoscale eddy track atlas product derived from the META3 altimetry version. 1exp DT allsat for trajectories and eddy properties (amplitude, eddy rotation speed and diameter), GEBCO_2022 grid data for bathymetry, ECMWF data at spatial resolution 1° x 1° for atmospheric pressure, and Copernicus Marine data at spatial resolution 0.25° x 0.25° for wind. The latitudes and longitudes of the daily eddy displacement points from their formation to their dissipation characterize the trajectories. We used two different approaches in our study. The first approach consist to put each endogenous variable as input for the FCM model, while the second approach utilized the endogenous variables multiplied by the multiple regression coefficients. The results conclude that the case where the input variables of the model are preprocessed by the multiple (linear or polynomial) regression operation before FCM modeling is the best approach.
利用ANFIS模糊C-Means模拟莫桑比克海峡中尺度反气旋涡旋的轨迹
本文的目的是优化ANFIS神经模糊系统的模糊C-Means (FCM)模型,以模拟莫桑比克海峡四种中尺度反气旋涡旋轨迹作为涡旋速度平均轮廓、振幅和直径、水平风、大气压和水深测量变量的函数。研究区域位于莫桑比克海峡东部,东经41°E-44°E,北纬16°S-25°S之间。根据涡旋轨迹的形成和消散带,将研究区感兴趣的涡旋轨迹分为四种类型。所使用的数据来自META3测高版的中尺度涡旋轨迹图集产品。1exp DT allsat用于轨迹和涡旋特性(振幅、涡旋转速和直径),GEBCO_2022网格数据用于测深,ECMWF数据用于大气压力,空间分辨率为1°x 1°,哥白尼海洋数据用于风,空间分辨率为0.25°x 0.25°。从涡旋形成到涡旋消散的日位移点的经纬度是涡旋轨迹的特征。我们在研究中使用了两种不同的方法。第一种方法包括将每个内生变量作为FCM模型的输入,而第二种方法利用内生变量乘以多元回归系数。结果表明,在FCM建模前对模型的输入变量进行多次(线性或多项式)回归运算预处理的情况是最佳方法。
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