基于虚拟传感器的坝区多输出自由场地震时程长序列预测模型研究OA北大核心CSTPCD
Research on multi-output seismic time-history long-term sequences prediction model for free field of dam based on virtual sensors
坝区自由场地震时程的多维长时序预测对于震害快速分析具有重要意义.虚拟传感器是地震物理传感器的补充感知手段,可实现地震时程的预测,然而现有虚拟传感器难以对多个信号做长时序预测,导致大坝震害分析较为滞后.针对上述问题,提出基于TFA-Seq2Seq虚拟传感器的坝区多输出自由场地震时程长序列预测模型.其中,基于多任务学习将Seq2Seq的虚拟传感器改进为"Encoder-3 Decoder"结构,以建立多个坝体物理传感器信号与自由场三个方向长时序地震时…查看全部>>
The multidimensional long-term prediction of seismic time-history in dam areas holds significant im-portance for rapid damage analysis.Virtual sensors,as complementary sensing mechanisms to seismic physical sensors,facilitate seismic time-history predictions.However,existing virtual sensors face challenges in effec-tively predicting long-term sequences for multiple signals,leading to delays in analyzing dam seismic damage.Addressing the aforementioned issue,…查看全部>>
苏哲;刘宗显;余红玲;佟大威;余佳;王晓玲
天津大学水利工程智能建设与运维全国重点实验室,天津 300072雅砻江流域水电开发有限公司,四川成都 610051中国农业大学水利与土木工程学院,北京 100083天津大学水利工程智能建设与运维全国重点实验室,天津 300072天津大学水利工程智能建设与运维全国重点实验室,天津 300072天津大学水利工程智能建设与运维全国重点实验室,天津 300072
水利科学
自由场地震虚拟传感器多输出长时序预测TFA-Seq2Seq多任务学习
free field seismicvirtual sensorsmulti-output long-term sequences predictionTFA-Seq2Seqmulti-task learning
《水利学报》 2024 (8)
966-976,989,12
天津市自然科学基金项目(22JCQNJC01150)
评论