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Keyphrases
XGBoost
100%
Machine Learning Techniques
100%
Fuzzy Inference System
100%
Multiple Faults
100%
Machine Learning Algorithms
100%
Induction Motor
100%
Classification Accuracy
66%
Predictive Maintenance
66%
Fault Classification
66%
Expert Opinion
33%
Big Data
33%
Machine Learning
33%
Fault Diagnosis
33%
Fault Detection
33%
Industrial Processes
33%
Machine Learning Models
33%
Extreme Gradient Boosting
33%
Feature Selection
33%
Accuracy Improvement
33%
Robustness to Noise
33%
Energy Efficiency
33%
Random Forest
33%
Support Vector Machine
33%
Condition Monitoring
33%
Explainability
33%
Threshold Method
33%
Fault Analysis
33%
Ensemble Learning
33%
Rotor Fault
33%
Human Experience
33%
Simultaneous Faults
33%
Comprehensibility
33%
Load Fluctuation
33%
Multi-fault
33%
Industrial Setting
33%
Three-phase Induction Motor
33%
Extreme Gradient Boosting(XGBoost)
33%
Gradient Boosting Machine
33%
K-nearest
33%
Ensemble Features
33%
Classification Robustness
33%
Rule-based Reasoning
33%
Energy Processes
33%
Industrial Motor
33%
Load Overvoltages
33%
Motor Condition Monitoring
33%
Fault Categorization
33%
Process Continuity
33%
Feature Interaction
33%
Concurrent Fault
33%
Active Maintenance
33%
Unbalanced Voltage
33%
AI-driven
33%
Industrial Applications
33%
Unplanned Downtime
33%
Voltage-current
33%
Intricate Relationships
33%
Fault Detection Method
33%
Key Operating Parameters
33%
Stator Winding
33%
Voltage-dependent Load
33%
Motor Fault
33%
Traditional Diagnostic Methods
33%
Motor Operations
33%
Real-time Fault Detection
33%
Engineering
Induction Motor
100%
Machine Learning Technique
100%
Xgboost
100%
Machine Learning Algorithm
75%
Fuzzy Inference
75%
Classification Accuracy
50%
Predictive Maintenance
50%
Fault Diagnosis
50%
Learning System
50%
Fault Detection
50%
Limitations
25%
Industrial Applications
25%
Feature Extraction
25%
Operating Parameter
25%
Expert Judgment
25%
Rotors
25%
Overvoltage
25%
Accident Prevention
25%
Condition Monitoring
25%
Random Forest
25%
Conservation of Energy
25%
Phase Induction Motor
25%
Artificial Intelligence
25%
Support Vector Machine
25%
Nearest Neighbor
25%
Big Data
25%
Unbalanced Voltage
25%
Interpretability
25%
Diagnosis
25%
Explainability
25%
Ensemble Learning
25%
Computer Science
Extreme Gradient Boosting
100%
Machine Learning Technique
100%
Inference System
50%
Machine Learning Algorithm
50%
Fault Diagnosis
33%
Classification Accuracy
33%
Fault Detection
33%
Big Data
16%
Random Decision Forest
16%
Feature Selection
16%
Traditional Method
16%
Ensemble Learning
16%
Unplanned Downtime
16%
Gradient Boosting
16%
Industrial Setting
16%
Active Maintenance
16%
Interpretability
16%
Energy Efficiency
16%
Detection Method
16%
Expert Judgment
16%
Condition Monitoring
16%
Human Experience
16%
Artificial Intelligence
16%
Machine Learning
16%
Learning System
16%
Industrial Applications
16%
Feature Extraction
16%
Comprehensibility
16%
rule based reasoning
16%
Feature Interaction
16%
Machine Learning Model
16%
Diagnosis
16%
Support Vector Machine
16%
Chemical Engineering
Learning System
100%
Xgboost
100%
Machine Learning Algorithm
75%
Artificial Intelligence
25%
Condition Monitoring
25%
Support Vector Machine
25%
Feature Extraction
25%