Flow Field Reconstruction and Prediction of Powder Fuel Transport Based on Scattering Images and Deep Learning
This paper presents the flow field reconstruction and prediction of powder fuel transport systems based on representative feature extraction from scattering images using deep learning techniques. A laboratory-built powder fuel supply system was used to conduct scattering spectroscopy experiments on...
Saved in:
| Main Authors: | Hongyuan Du, Zhen Cao, Yingjie Song, Jiangbo Peng, Chaobo Yang, Xin Yu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/15/4613 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
“Optimizing sEMG Gesture Recognition with Stacked Autoencoder Neural Network for Bionic Hand”
by: Mr. Amol Pandurang Yadav, et al.
Published: (2025-06-01) -
Speech emotion recognition based on a stacked autoencoders optimized by PSO based grass fibrous root optimization
by: Chi Zeng, et al.
Published: (2025-07-01) -
ST-MSRN: An enhanced spatio-temporal super-resolution model for complex meteorological data reconstruction
by: Ping Mei, et al.
Published: (2025-08-01) -
Enhancing Weather Monitoring for Agriculture with Deep Learning: Anomaly Detection in East Java Using LSTM Autoencoder and OCSVM
by: Maulana Ahsan Fadillah, et al.
Published: (2025-06-01) -
MASFF-Net: Multiazimuth Scattering Feature Fusion Network for SAR Target Recognition
by: Huiqiang Zhang, et al.
Published: (2025-01-01)