RSST-ARGM: a data-driven approach to long-term sea surface temperature prediction

EURASIP Journal on Wireless Communications and Networking

Yonghong Zhang¹  Qi Liu²  Xiaodong Liu³  Linqian Zhu⁴ 

[1] School of Automation, Nanjing University of Information Science and Technology, Nanjing, China;School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China;School of Computing, Edinburgh Napier University, Edinburgh, Scotland, UK;School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China;

关键词: Long-term prediction;    Regional SST;    Temperature variation;    Grey model;    Atmospheric reflection;   

DOI  :  10.1186/s13638-021-02044-9

来源: Springer

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