江苏水利Issue(9)：24-29,6.
基于MDN和VMD-TPA-LSTM的泵站主机组劣化趋势预测
Deterioration trend prediction of pump station host group based on MDN and VMD-TPA-LSTM
摘要
Abstract
In order to improve the safe and stable operation capability of the pump station host group,analyze its operating status,obtain the health status of the unit equipment,and accurately predict its future development trend,a pump station host group degradation trend prediction model based on Mixed Density Networks(MDN),Variational Mode Decomposition(VMD),and Temporal Pattern Attention Long Short Term Memory Network(TPA-LSTM)based on temporal pattern and attention mechanism is proposed.The simulation results show that this method can accurately express the deterioration trend of the unit and effectively improve its prediction accuracy.关键词
趋势预测/网络模型/泵站机组/MDN/VMD/TPA-LSTMKey words
trend prediction/network model/pump station unit/MDN/VMD/TPA-LSTM分类
建筑与水利引用本文复制引用
夏臣智,李英玉,吴子豪,李超顺,黃富佳,莫兆祥..基于MDN和VMD-TPA-LSTM的泵站主机组劣化趋势预测[J].江苏水利,2024,(9):24-29,6.基金项目
江苏省水利科技项目(2022001) （2022001）
