首页|期刊导航|Big Data Mining and Analytics|LSTM-KAN:Revolutionizing Indoor Visible Light Localization with Robust Sequence Learning

LSTM-KAN:Revolutionizing Indoor Visible Light Localization with Robust Sequence Learning

Yonghao Yu Dawei Zhao Junjun Chen Kexue Fu Shui Yu Longxiang Gao Khandakar Ahmed Youyang Qu

Big Data Mining and Analytics2025，Vol.8Issue(6)：P.1245-1260,16.

Big Data Mining and Analytics2025，Vol.8Issue(6)：P.1245-1260,16.DOI:10.26599/BDMA.2025.9020021

LSTM-KAN:Revolutionizing Indoor Visible Light Localization with Robust Sequence Learning

Yonghao Yu ¹Dawei Zhao ²Junjun Chen ³Kexue Fu ²Shui Yu ⁴Longxiang Gao ²Khandakar Ahmed ⁵Youyang Qu²

作者信息

1. Faculty of Data Science,City University of Macao,Macao 999078,China
2. Key Laboratory of Computing Power Network and Information Security of Ministry of Education,Shandong Computer Science Center,Qilu University of Technology(Shandong Academy of Sciences),Jinan 250014,China
3. Computer Center,Peking University,Beijing 100871,China
4. School of Computer Science,University of Technology Sydney,Ultimo 2007,Australia
5. College of Engineering and Science,Victoria University,Melbourne,AU 3011,Australia
折叠

摘要

关键词

indoor visible light positioning/sequence feature/deep learning

分类

信息技术与安全科学

引用本文复制引用

Yonghao Yu,Dawei Zhao,Junjun Chen,Kexue Fu,Shui Yu,Longxiang Gao,Khandakar Ahmed,Youyang Qu..LSTM-KAN:Revolutionizing Indoor Visible Light Localization with Robust Sequence Learning[J].Big Data Mining and Analytics,2025,8(6):P.1245-1260,16.

基金项目

supported by the National Key R&D Program of China(No.2023YFB3107303) （No.2023YFB3107303）

the National Natural Science Foundation of China(No.62172244) （No.62172244）

the Young Innovation Team of Colleges and Universities in Shandong Province(No.2021KJ001) （No.2021KJ001）

the Taishan Scholars Program(No.TSQNZ20230621) （No.TSQNZ20230621）

the Shandong Provincial Natural Science Foundation(No.ZR202211150015) （No.ZR202211150015）

the“20 New Universities”Project of Jinan City(No.202333045). （No.202333045）

Big Data Mining and Analytics

OACSCD

ISSN：2096-0654

访问量0

下载量0

段落导航