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AS-SOMTF:A novel multi-task learning model for water level prediction by satellite remoting

Xin Su Zijian Qin Weikang Feng Ziyang Gong Christian Esposito Sokjoon Lee

Digital Communications and Networks2025，Vol.11Issue(5)：P.1554-1566,13.

Digital Communications and Networks2025，Vol.11Issue(5)：P.1554-1566,13.DOI:10.1016/j.dcan.2025.05.006

AS-SOMTF:A novel multi-task learning model for water level prediction by satellite remoting

Xin Su ¹Zijian Qin ¹Weikang Feng ¹Ziyang Gong ²Christian Esposito ³Sokjoon Lee²

作者信息

1. The College of Information Science and Engineering,Hohai University,Changzhou 213200,China
2. The Department of Computer Engineering,Gachon University,Seongnam 13120,South Korea
3. The Department of Computer Science,University of Salerno,Fisciano I-84084,Italy
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摘要

关键词

Fish passages/Water-level prediction/Time series forecasting/Multi-task learning/Hierarchical clustering/Satellite communication

分类

农业科技

引用本文复制引用

Xin Su,Zijian Qin,Weikang Feng,Ziyang Gong,Christian Esposito,Sokjoon Lee..AS-SOMTF:A novel multi-task learning model for water level prediction by satellite remoting[J].Digital Communications and Networks,2025,11(5):P.1554-1566,13.

基金项目

supported in part by the National Natural Science Foundation of China under Grant 62371181 （）

in part by the Changzhou Science and Technology International Cooperation Program under Grant CZ20230029 （）

The Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2024-00396797,Development of core technology for intelligent O-RAN security platform). （IITP）

Digital Communications and Networks

ISSN：2468-5925

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