Semi-Autogenous Mill Power Consumption Prediction Based on CACN-LSTM
The semi-autogenous (SAG) mill is crucial equipment in the beneficiation process, and power consumption is a key indicator of its operational status. Due to the complex and variable operating environment, the power consumption of the SAG mill has the characteristics of strong coupling of multiple fa...
Saved in:
Main Authors: | Dingchao Zhang, Xin Xiong, Chongyang Shao, Yao Zeng, Jun Ma |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/1/2 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Relation extraction based on CNN and Bi-LSTM
by: Xiaobin ZHANG, et al.
Published: (2018-09-01) -
Energy consumption prediction using modified deep CNN-Bi LSTM with attention mechanism
by: Adel Binbusayyis, et al.
Published: (2025-01-01) -
LIFE PREDICTION OF ROLLING BEARING BASED ON MULTI-RESOLUTION SINGULAR VALUE DECOMPOSITION AND ECNN-LSTM
by: XIONG Jun, et al.
Published: (2021-01-01) -
FBiLSTM-Attention short-term load forecasting based on fuzzy logic
by: Yan ZHANG, et al.
Published: (2025-02-01) -
BMNet: Enhancing Deepfake Detection Through BiLSTM and Multi-Head Self-Attention Mechanism
by: Demao Xiong, et al.
Published: (2025-01-01)