Results 41 to 50 of about 38,147 (211)

An Improved VMD-LSTM Model for Time-Varying GNSS Time Series Prediction with Temporally Correlated Noise

Remote Sensing, 2023
GNSS time series prediction plays a significant role in monitoring crustal plate motion, landslide detection, and the maintenance of the global coordinate framework.
Hongkang Chen, Tieding Lu, Jiahui Huang, Xiaoxing He, Kegen Yu, Xiwen Sun, Xiaping Ma, Zhengkai Huang   +7 more
semanticscholar   +1 more source

Monthly runoff prediction based on a coupled VMD-SSA-BiLSTM model

Scientific Reports, 2023
The accurate prediction of monthly runoff in the lower reaches of the Yellow River is crucial for the rational utilization of regional water resources, optimal allocation, and flood prevention.
Xianqi Zhang, X. Wang, Haiyang Li, Shifeng Sun, Fang Liu   +4 more
semanticscholar   +1 more source

A denoising method for concrete cracking electromagnetic signals based on grey wolf optimized VMD-WT

Diance yu yibiao
In the moment of concrete cracking, electromagnetic signals are generated due to the oscillation of surface charges on the cracks. Aiming at the issue of electromagnetic signals being susceptible to environmental noise interference and having a low ...
HOU Chunyao, TAN Dawen, MAO Yanpian, ZHANG Hongyi, ZHOU Yi, ZHANG Jinghua, HUANG Songling   +6 more
doaj   +1 more source

Neural Network-Based Hybrid Forecasting Models for Time-Varying Passenger Flow of Intercity High-Speed Railways

Mathematics, 2022
Time-varying passenger flow is the input data in the optimization design of intercity high-speed railway transportation products, and it plays an important role.
Huanyin Su, Shuting Peng, Shanglin Mo, Kaixin Wu   +3 more
doaj   +1 more source

A Rolling Bearing Fault Diagnosis Method Based on the WOA-VMD and the GAT

Entropy, 2023
In complex industrial environments, the vibration signal of the rolling bearing is covered by noise, which makes fault diagnosis inaccurate. In order to overcome the effect of noise on the signal, a rolling bearing fault diagnosis method based on the WOA-
Yaping Wang, Shenmin Zhang, Ruofan Cao, Di Xu, Yuqi Fan   +4 more
semanticscholar   +1 more source

Improved monthly runoff time series prediction using the CABES-LSTM mixture model based on CEEMDAN-VMD decomposition

Journal of Hydroinformatics, 2023
Accurate runoff prediction is vital in optimizing reservoir scheduling, efficiently managing water resources, and ensuring the effective utilization of water resources.
Dong-mei Xu, An-dong Liao, Wen-chuan Wang, Wei-can Tian, Hong-fei Zang   +4 more
semanticscholar   +1 more source

Research on data-driven and correlation-based electric energy error analysis method

Diance yu yibiao
A supplementary strategy is proposed to use operational errors as a reliable source of load point errors in traditional methods, in response to the problem of insufficient detection of load points in electric energy meters and the inability of some load ...
RONG Xueqin, DING Yingying, LIU Yong
doaj   +1 more source

Electric vehicle charging load prediction method based on multi-objective modal decomposition and NAHL neural network

Diance yu yibiao
To improve the accuracy of electric vehicle charging load prediction, a prediction method based on multi-objective variational mode decomposition (VMD) and automatic artificial neural network with an augmented hidden layer (NAHL) is proposed.
GUO Xinzhe, WANG Yeqin, WANG Chao, WU Mingjiang, YANG Yan, ZHANG Chu   +5 more
doaj   +1 more source

Multi-feature stock price prediction by LSTM networks based on VMD and TMFG

Journal of Big Data
The stock market is characterized by its high nonlinearity and complexity, making traditional methods ineffective in capturing its nonlinear features and complex market dynamics.
Zhixin Zhang, Qingyang Liu, Yanrong Hu, Hongjiu Liu   +3 more
semanticscholar   +1 more source

A VMD and LSTM Based Hybrid Model of Load Forecasting for Power Grid Security

IEEE Transactions on Industrial Informatics, 2022
As the basis for the static security of the power grid, power load forecasting directly affects the safety of grid operation, the rationality of grid planning, and the economy of supply–demand balance.
L. Lv, Zongyuan Wu, Jinhua Zhang, Zhiyuan Simon Tan, Lei Zhang, Z. Tian   +5 more
semanticscholar   +1 more source