Sökresultat - "complete ensemble empirical mode decomposition with adaptive noise"

Identification of patients with de novo Parkinson's Disease from chemosensory EEG signals using ICEEMDAN domain Entropy Features

De, S., Pavuluri, S., Gupta, A.K.

Investigation of Mechanical Fault Diagnosis Methods for On-Load Tap Changer Based on Texture Features of Curved-Surface Images Reconstructed in Phase Space

Qi, R., Zhao, T., Wei, B., Peng, B., Chen, Z., Wang, X.

A Lithium-Ion Battery RUL Prediction Method Based on ConvTrans and tAPE Under Capacity Regeneration Noise and Low-Dimensional Time Series Data

Chen, J., Lu, Q., Wang, X., Ge, H., Xie, M.

A Reconstruction Method for Weak Magnetic Pipeline Inspection Signals Based on Adaptive Multiscale Signal Reconstruction

Liu, B., Liu, Y., Lian, Z., Wu, Z., He, L., Yang, L.

An Improved OTDR Signal Denoising Method Based on ICEEMDAN-NLM Algorithm

Zhang, F., Ran, H., Li, B., Zhang, X., Guo, L., Gong, X.

Forecasting Dissolved Oxygen Based on Two-Stage Decomposition with BiLSTM-Attention and weighted Huber Loss Function

Pant, Neha, Toshniwal, Durga, Gurjar, Bhola Ram

2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA)

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Predicting the Remaining Useful Life of Lithium-ion Batteries with Mode-Gating Network

Fan, Xianguo, Yin, Chengqi, Mu, Xianmin, Lv, Xiangnan, Yan, Wenqian, Duan, Changjiang

2024 6th International Conference on Energy, Power and Grid (ICEPG)

Sleep staging method based on CEEMDAN-WPD algorithm

Fang, Yu, Deng, Daishen, Liu, Dongbo, Wang, Weibo

2024 3rd International Conference on Electronics and Information Technology (EIT)

Short-term Power Load Forecasting Based on Multiple Load Characteristics and TCN-GRU Combined Model

Han, Wenxuan, Yan, Yuehao, Li, Zongwen, Zhao, Yunfei, Chang, Yizhe

2024 2nd International Conference on Algorithm, Image Processing and Machine Vision (AIPMV)

Identification of Pipeline Intrusion Signals Based on ICEEMDAN-FE-AIT and F-ELM in the uwDAS System

Ran, C., Xiao, P., Luo, Z., Chen, X.

Short-Term Photovoltaic Power Prediction Based on CEEMDAN and Hybrid Neural Networks

Wu, S., Guo, H., Zhang, X., Wang, F.

Dynamic Combination Forecasting for Short-Term Photovoltaic Power

Huang, Y., Liu, J., Zhang, Z., Li, D., Li, X., Wang, G.

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A New Radio Frequency Fingerprint Identification Method Based on CEEMDAN

Yang, Weikang, Zhao, Jianing, Xue, Shaoxuan, Wang, Xin, Ni, Xuenan

2024 International Wireless Communications and Mobile Computing (IWCMC)

Air quality prediction based on ICEEMDAN-SSA-LSTM

Qin, Yanling, Ma, Hongyan, He, Wei

2024 36th Chinese Control and Decision Conference (CCDC)

Remaining Useful Life Prediction of Lithium-Ion Batteries Based on CEEMDAN-Bi-LSTM Hybrid Model

Zheng, Di, Man, Shuo, Ning, Yi

2024 Second International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)

Real-time heart rate detection based on body surface video data

Bai, Jiayuan, Wei, Bing, Zhong, Jin

2024 3rd International Conference on Image Processing and Media Computing (ICIPMC)

Ultra-Short-Term Wind Speed Prediction Based on ICEEMDAN and SSA-LSTM

Wang, Yupeng, Zhang, Zhenbin, Li, Haitao, Li, Zhen, Wang, Yilin

2024 IEEE 7th International Electrical and Energy Conference (CIEEC）

Demand Planning and Forecasting in the High Technology Industry Based on Hybrid CEEMDAN-GA-BPNN Model

Vasundhara, S., Ameen, Nabeena, Maragatham, R. Stella, Kumar Lamba, Anil, Vijayakumar, E., Nishant, Neerav

2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC)