Enhancing the accuracy of real-time ship roll prediction is crucial for maritime safety and operational efficiency.To address the challenge of accurately predicting the ship roll status with nonlinear time-varying dyn...Enhancing the accuracy of real-time ship roll prediction is crucial for maritime safety and operational efficiency.To address the challenge of accurately predicting the ship roll status with nonlinear time-varying dynamic characteristics,a real-time ship roll prediction scheme is proposed on the basis of a data preprocessing strategy and a novel stochastic trainer-based feedforward neural network.The sliding data window serves as a ship time-varying dynamic observer to enhance model prediction stability.The variational mode decomposition method extracts effective information on ship roll motion and reduces the non-stationary characteristics of the series.The energy entropy method reconstructs the mode components into high-frequency,medium-frequency,and low-frequency series to reduce model complexity.An improved black widow optimization algorithm trainer-based feedforward neural network with enhanced local optimal avoidance predicts the high-frequency component,enabling accurate tracking of abrupt signals.Additionally,the deterministic algorithm trainer-based neural network,characterized by rapid processing speed,predicts the remaining two mode components.Thus,real-time ship roll forecasting can be achieved through the reconstruction of mode component prediction results.The feasibility and effectiveness of the proposed hybrid prediction scheme for ship roll motion are demonstrated through the measured data of a full-scale ship trial.The proposed prediction scheme achieves real-time ship roll prediction with superior prediction accuracy.展开更多
The structure and processes of nickel induced lateral crystallization are studied.The structure of metal induced lateral crystallization(MILC) is improved by opening a seed window on the buried oxide,which is helpfu t...The structure and processes of nickel induced lateral crystallization are studied.The structure of metal induced lateral crystallization(MILC) is improved by opening a seed window on the buried oxide,which is helpfu to get superior quality of large grain poly Si at low temperature.By optimizing the temperature and time of annealing based on others' pervious work,the large grain poly Si with few defects are obtained,and the typical grain size is 70～80μm.The methods of etching NiSi 2 which is created after the long time annealing are also studied for the first time.Finally,a method is successfully chosen to reduce the possible contamination of Ni and to guarantee the MILC for the submicron VLSI application.展开更多
我们单位各办公楼之间的距离较大，所以常使用远程桌面连接来对服务器进行远程管理和维护。一日，有位同事来电称，她想用Windows XP远程桌面连接服务器机房的Widows Server 2003服务器，对他们设在该服务器上的Web站点进行维护，多次...我们单位各办公楼之间的距离较大，所以常使用远程桌面连接来对服务器进行远程管理和维护。一日，有位同事来电称，她想用Windows XP远程桌面连接服务器机房的Widows Server 2003服务器，对他们设在该服务器上的Web站点进行维护，多次试连，均未能连上。展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.52231014 and 52271361)the Natural Science Foundation of Guangdong Province of China(Grant No.2023A1515010684).
文摘Enhancing the accuracy of real-time ship roll prediction is crucial for maritime safety and operational efficiency.To address the challenge of accurately predicting the ship roll status with nonlinear time-varying dynamic characteristics,a real-time ship roll prediction scheme is proposed on the basis of a data preprocessing strategy and a novel stochastic trainer-based feedforward neural network.The sliding data window serves as a ship time-varying dynamic observer to enhance model prediction stability.The variational mode decomposition method extracts effective information on ship roll motion and reduces the non-stationary characteristics of the series.The energy entropy method reconstructs the mode components into high-frequency,medium-frequency,and low-frequency series to reduce model complexity.An improved black widow optimization algorithm trainer-based feedforward neural network with enhanced local optimal avoidance predicts the high-frequency component,enabling accurate tracking of abrupt signals.Additionally,the deterministic algorithm trainer-based neural network,characterized by rapid processing speed,predicts the remaining two mode components.Thus,real-time ship roll forecasting can be achieved through the reconstruction of mode component prediction results.The feasibility and effectiveness of the proposed hybrid prediction scheme for ship roll motion are demonstrated through the measured data of a full-scale ship trial.The proposed prediction scheme achieves real-time ship roll prediction with superior prediction accuracy.
文摘The structure and processes of nickel induced lateral crystallization are studied.The structure of metal induced lateral crystallization(MILC) is improved by opening a seed window on the buried oxide,which is helpfu to get superior quality of large grain poly Si at low temperature.By optimizing the temperature and time of annealing based on others' pervious work,the large grain poly Si with few defects are obtained,and the typical grain size is 70～80μm.The methods of etching NiSi 2 which is created after the long time annealing are also studied for the first time.Finally,a method is successfully chosen to reduce the possible contamination of Ni and to guarantee the MILC for the submicron VLSI application.
