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Table 2 Other statistical and soft computing models for SST prediction

From: Applications of soft computing models for predicting sea surface temperature: a comprehensive review and assessment

Scholars

Model

Compared model

Case studies

Source of data

Period of data

Performance indices

Inputs

(Huang et al. 2007)

ANFIS

–

Taiwan

Argo Data base

http://www.argo.ucsd.edu,

http://argo.jcommops.org

January 2001 to December 2005

-

Salinity, temperature, radius, angle, time

(Huang et al. 2008b)

FIS

–

Taiwan

Argo Data Base

http://www.argo.ucsd.edu

http://www.usgodae.org/argo/argo.html

January 2001 to December 2006

Entropy

Salinity, Temperature

(Shirvani et al. 2015)

ARMA

ARIMA

Persian Gulf (Indian Ocean)

ERSST.v3, OISST

http://www.ncdc.noaa.gov/oa/climate/research/sst/oi-daily-information.php

1950–2011

RMSE

Monthly

SST (1-3)

(Awan and Bae 2016)

ANFIS

–

East Asian (Indian Ocean and Pacific)

APHRODITE

ERSST v3b

http://www1.ncdc.noaa.gov/pub/data/cmb/ersst/v3b

1978–2002

R, RMSE

SPI, SST, SSTA

(Salles et al. 2016)

ARIMA, Random Walk

 

Tropical Atlantic Ocean

PIRATA Buoys

January 1998 to March 2015

MSE, NMSE, MAPE, SMAPE

Lagged SST

(LI et al. 2017)

SVM-CEEMD

 

Northeast Pacific Ocean

(Bond et al. 2015)

1982–2015

R, RMSE, AE

SSTA

(Jiang et al. 2018b)

SVR

LR

Canadian Berkeley Canyon

WOA13, BOA, Argo, ONC

2004-2015

MSE, SCC

Longitude, latitude (Y), depth, spatial data