Application of Deep Learning in Predicting Particle Concentration of Gas–Solid Two-Phase Flow
Particle concentration is an important parameter for describing the state of gas–solid two-phase flow. This study compares the performance of three methods, namely, Back-Propagation Neural Networks (BPNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM), in handling gas–solid tw...
| Main Authors: | , , |
|---|---|
| 格式: | 文件 |
| 语言: | English |
| 出版: |
MDPI AG
2024-02-01
|
| 丛编: | Fluids |
| 主题: | |
| 在线阅读: | https://www.mdpi.com/2311-5521/9/3/59 |