Classification and identification of extreme wind events by CNNs based on Shapelets and improved GASF-GADF-Reference-Cited by-同舟云学术

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Classification and identification of extreme wind events by CNNs based on Shapelets and improved GASF-GADF

Published:2024-10 Issue: Volume:253 Page:105852
ISSN:0167-6105
Container-title:Journal of Wind Engineering and Industrial Aerodynamics
language:en
Short-container-title:Journal of Wind Engineering and Industrial Aerodynamics

Author:

Chen Liujie,Xu Denghua,Yang Le,Ng Ching-Tai,Fu Jiyang^ORCID,He Yuncheng,He Yinghou

Publisher

Elsevier BV

Reference64 articles.

1. Well-testing model identification using time-series shapelets;Ahmadi;J. Petrol. Sci. Eng.,2017

2. Applications of shapelet transform to time series classification of earthquake, wind and wave data;Arul;Eng. Struct.,2021

3. Data anomaly detection for structural health monitoring of bridges using shapelet transform;Arul;Smart Struct. Syst.,2022

4. Machine learning based automated identification of thunderstorms from anemometric records using shapelet transform;Arul;J. Wind Eng. Ind. Aerod.,2022

5. The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances;Bagnall;Data Min. Knowl. Discov.,2017

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