A5100670532- Fault Detection and Control Systems
- Neural Networks and Applications
- Advanced Algorithms and Applications
- Mineral Processing and Grinding
- Advanced Data Processing Techniques
- Spectroscopy and Chemometric Analyses
- Advanced Malware Detection Techniques
- Industrial Technology and Control Systems
- Advanced Statistical Process Monitoring
- Water Quality Monitoring and Analysis
- Traffic Prediction and Management Techniques
- Simulation and Modeling Applications
- Advanced Chemical Sensor Technologies
- Chinese history and philosophy
- Advanced Sensor and Control Systems
- Industrial Vision Systems and Defect Detection
- Network Security and Intrusion Detection
- Machine Fault Diagnosis Techniques
- Time Series Analysis and Forecasting
- Geoscience and Mining Technology
- Metal Alloys Wear and Properties
- Hydrocarbon exploration and reservoir analysis
- Digital Media Forensic Detection
- Advanced Battery Technologies Research
- Anomaly Detection Techniques and Applications
Ministry of Public Security of the People's Republic of China
2017-2024
Southeast University
2022-2024
Sichuan University
2024
Jimei University
2008-2023
Anhui University of Technology
2022-2023
Ministry of Education of the People's Republic of China
2022-2023
Wuhan Institute of Technology
2023
North China Institute of Science and Technology
2022
City University of Hong Kong
2021
Geely (China)
2021
Spare parts management is a critical issue in the industrial field, alongside planning maintenance and logistics activities. For accurate classification particular, decision-makers can determine optimal inventory strategy. However, problems such as criteria selection, rules explanatory, learning ability arise when managing thousands of spare for modern industry. This paper presents deep convolutional neural network based on graph (G-DCNN) which will realize multi-criteria through image...
Due to rich characteristics and functionalities, PDF format has become the de facto standard for electronic document exchange. As vulnerabilities in major viewers have been disclosed, a number of methods proposed tame increasing threats. However, one recent evasion exploit is found evade most detections renders all static void. Moreover, many existing identified before can now detection through exploiting this exploit. In paper, we introduce newly propose new feature extractor FEPDF detect...
Abstract Advancements in information technology have made various industrial equipment increasingly sophisticated recent years. The remaining useful life (RUL) of plays a crucial important role the process. It is difficult to establish functional RUL model as it requires fusion time‐series data across different scales. This paper proposes long‐short term memory neural network, which integrates novel partial least square based on genetic algorithm (GAPLS‐LSTM). parameters are first analyzed...
With developments of deep learning technologies and increasing demands for industrial process feature extractions, researchers pay much attention to historical data. Currently, the convolutional neural network (CNN) has made progress into extracting potential features from plant However, existing sliding window associated with CNNs is rarely concerned characteristics data such as slow time varying variable correlations. In response this problem, an improved bar-shaped CNN (IBS-CNN) tailored...