艾明曦｜云南大学｜学者主页

2026

基于专家经验引导的浮选泡沫图像表征学习

张进，黄嘉豪，艾明曦，唐朝晖，谢永芳，马军

《自动化学报》

2026

基于浅层特征与深层特征融合的浮选工况识别

艾明曦，孔庆洁，张进，许庆，李鹏，谢永芳，唐朝晖

《控制理论与应用》

2026

Prediction error-guided gated fusion of shallow and deep spatiotemporal features for flotation working condition recognition

Qingjie Kong, Jinyu Zhang, Qingfang Chen, Mingxi Ai, Jin Zhang, Yongfang Xie, Zhaohui Tang

Minerals Engineering

DOI

2026

Adaptive temporal sparse manifold representation for reliable fault detection in multimode industrial processes

Hancheng Wang, Peng Li, Mingxi Ai, Chuangyan Yang, Jiande Wu

Control Engineering Practice

DOI

2026

Continual Learning Visual Sensing Network for Flotation Process Monitoring

Jin Zhang, Mingxi Ai, Zhaohui Tang, Yongfang Xie

IEEE Transactions on Industrial Informatics

DOI

2026

Noise-robust contrastive ensemble learning for flotation process monitoring

Mingxi Ai, Jin Zhang, Tang Zh, Yongfang Xie

Chemometrics and Intelligent Laboratory Systems

DOI

2025

基于局部特征增强的浮选过程改进半监督工况识别方法

艾明曦，许庆，张进，孔庆洁，李鹏，谢永芳，唐朝晖

《控制与决策》

2025

Multimodal EKF–MPPCA model for Anomaly Detection in Complex Dynamic Industrial Processes

Chuangyan Yang, Peng Li, Jiande Wu, Mingxi Ai, Hancheng Wang, Fei Tao

China Automation Congress (CAC)

DOI

2025

Adaptive chemical industrial processes fault detection model based on Sparse Filtering-based Improved Mixed-Gaussian Probabilistic Principal Component Analysis considering low-probability events

Chuangyan Yang, Jiande Wu, Peng Li, Xun Lang, Mingxi Ai, Hancheng Wang

Engineering Applications of Artificial Intelligence

DOI

2025

Temperature Prediction in Discrete-Continuous Hybrid Tin Chemical Process Using Trapezoidal Rule and Improved Stochastic Configuration Networks

Chuangyan Yang, Peng Li, Mingxi Ai, Jiande Wu

IEEE Transactions on Industrial Electronics

DOI

2025

Semi-supervised contrastive learning for flotation process monitoring with uncertainty-aware prototype optimization

Mingxi Ai, Jin Zhang, Peng Li, Jiande Wu, Zhaohui Tang, Yongfang Xie

Engineering Applications of Artificial Intelligence

DOI

2025

Data-Efficient Soft Sensing Learning for Flotation Process Monitoring

Jin Zhang, Mingxi Ai, Zhaohui Tang, Yongfang Xie, Jiande Wu, Jun Ma

IEEE Transactions on Instrumentation and Measurement

DOI

2025

A Sentinel-Based Adaptive Hybrid Soft Sensing Method for Industrial Process Monitoring

Jin Zhang, Mingxi Ai, Zhaohui Tang, Yongfang Xie, Jun Ma, Jiande Wu

IEEE Transactions on Instrumentation and Measurement

DOI

2025

Forward Selection Component Variable and Dynamic Inner Manifold Learning for Process Monitoring

Hancheng Wang, Peng Li, Jiande Wu, Mingxi Ai, Chuangyan Yang

IEEE Transactions on Instrumentation and Measurement

DOI

2024

Temperature Control Method for Batch Reactors Based on Adaptive Delay Compensation

Dehui Mao, Peng Li, Mingxi Ai, Jiande Wu, Chuangyan Yang, Hancheng Wang

China Automation Congress (CAC)

DOI

2024

Complex Industrial Process Monitoring using Improved Dynamic Latent Variables - Neighborhood Preserving Embedding

Hancheng Wang, Peng Li, Mingxi Ai, Jiande Wu, Chuangyan Yang, XU Qingmin

China Automation Congress (CAC)

DOI

2024

Gaussian-kernel weighted neighborhood preserving embedding algorithm and its application in fault detection

Hancheng Wang, Peng Li, Mingxi Ai, Jiande Wu, Chuangyan Yang, Deen Pan

Measurement Science and Technology

DOI

2023

Semisupervised Contrastive Memory Network for Industrial Process Working Condition Monitoring

Zhaohui Tang, Jin Zhang, Yongfang Xie, Steven X. Ding, Mingxi Ai

IEEE Transactions on Instrumentation and Measurement

DOI

2022

Generative adversarial network-based image-level optimal setpoint calculation for flotation reagents control

Jin Zhang, Zhaohui Tang, Yongfang Xie, Mingxi Ai, Weihua Gui

Expert Systems With Applications，Vol. 197

DOI

2021

Visual Perception-Based Fault Diagnosis in Froth Flotation Using Statistical Approaches

Jin Zhang, Zhaohui Tang, Yongfang Xie, Mingxi Ai, Weihua Gui

Tsinghua Science and Technology

2020

基于复原图像特征与深度视觉特征融合的锑粗选异常工况识别

保江，谢永芳，刘金平，唐朝晖，艾明曦

《控制理论与应用》

艾明曦

精选作品

期刊论文

基于专家经验引导的浮选泡沫图像表征学习

基于浅层特征与深层特征融合的浮选工况识别

Prediction error-guided gated fusion of shallow and deep spatiotemporal features for flotation working condition recognition

Adaptive temporal sparse manifold representation for reliable fault detection in multimode industrial processes

Continual Learning Visual Sensing Network for Flotation Process Monitoring

Noise-robust contrastive ensemble learning for flotation process monitoring

基于局部特征增强的浮选过程改进半监督工况识别方法

Multimodal EKF–MPPCA model for Anomaly Detection in Complex Dynamic Industrial Processes

Adaptive chemical industrial processes fault detection model based on Sparse Filtering-based Improved Mixed-Gaussian Probabilistic Principal Component Analysis considering low-probability events

Temperature Prediction in Discrete-Continuous Hybrid Tin Chemical Process Using Trapezoidal Rule and Improved Stochastic Configuration Networks

Semi-supervised contrastive learning for flotation process monitoring with uncertainty-aware prototype optimization

Data-Efficient Soft Sensing Learning for Flotation Process Monitoring

A Sentinel-Based Adaptive Hybrid Soft Sensing Method for Industrial Process Monitoring

Forward Selection Component Variable and Dynamic Inner Manifold Learning for Process Monitoring

Temperature Control Method for Batch Reactors Based on Adaptive Delay Compensation

Complex Industrial Process Monitoring using Improved Dynamic Latent Variables - Neighborhood Preserving Embedding

Gaussian-kernel weighted neighborhood preserving embedding algorithm and its application in fault detection

Semisupervised Contrastive Memory Network for Industrial Process Working Condition Monitoring

Generative adversarial network-based image-level optimal setpoint calculation for flotation reagents control

Visual Perception-Based Fault Diagnosis in Froth Flotation Using Statistical Approaches

基于复原图像特征与深度视觉特征融合的锑粗选异常工况识别

会议论文

Multi-view Topological Manifold Data Analytics and Multimodal Industrial Process Monitoring

Representation-Enhanced Semi-Supervised Learning for Flotation Working Condition Recognition

Timed key-value memory network for flotation reagent control

Flotation Feed Grade Estimation Based on Spatial-Temporal Correlation Analysis of Froth Image Features

预印本

Multivariate Statistical Process Monitoring Method Considering Low Probability Events for Process Fault Detection

研究方向