Data-driven approach for labelling process plant event data

Earth and Planetary Sciences

• Labelling 100%
• Datum 100%
• Plant 100%
• Model 50%
• Data Set 41%
• Ground Truth 25%
• Response 25%
• Detection 25%
• Interest 16%
• Investigation 16%
• Strategy 16%
• Rule 16%
• Month 16%
• Time Series 8%
• Control System 8%
• Logistics 8%
• Historical Record 8%
• Anomaly 8%
• Fault Detection 8%
• Time 8%
• Support 8%
• Set 8%
• Experiment 8%
• Failure 8%
• Impact 8%
• Environment 8%
• Decision 8%
• Selection 8%
• Service 8%
• Laboratory 8%
• Industry 8%
• Increasing 8%
• Requirement 8%
• Estimate 8%
• Forest 8%
• Fault 8%
• Data Processing 8%
• Parameter 8%
• Regression 8%

Computer Science

• Driven Approach 100%
• Events 100%
• Models 41%
• Response Variable 25%
• Event Detection 16%
• Case Study 8%
• Simulated Data 8%
• In-Process 8%
• Hierarchical Clustering 8%
• Random Decision Forest 8%
• Industrial Environment 8%
• Logistic Regression Model 8%
• Historical Event 8%
• Fault Detection 8%
• Fundamental Importance 8%
• Historical Record 8%
• Process Control System 8%
• Anomaly Detection 8%
• Service 8%
• Data Analysis 8%
• Sensor 8%
• False Positive 8%

Mathematics

• Events 100%
• Data Set 41%
• Detection 33%
• Response Variable 25%
• Selection 16%
• Imbalance 16%
• Test Set 8%
• Logistic Regression Model 8%
• Sensor 8%
• Simulated Data 8%
• Year Period 8%
• Raise Question 8%
• Anomalies 8%
• Control System 8%
• Hierarchical Clustering 8%
• Binary Response 8%
• Parameters 8%
• Number 8%