A machine learning and genetic algorithm-based method for predicting width deviation of hot-rolled strip in steel production systems

Mathematics

• Production Systems 90%
• Steel 81%
• Learning Algorithm 80%
• Machine Learning 74%
• Genetic Algorithm 73%
• Prediction Model 69%
• Strip 64%
• Deviation 61%
• Interpretability 53%
• Prediction 43%
• Linear regression 26%
• Hot Rolling 24%
• Hybrid Method 15%
• Industry 13%
• Trade-offs 13%
• Divides 13%
• Metric 8%
• Model 8%
• Performance 8%

Business & Economics

• Genetic Algorithm 100%
• Machine Learning 89%
• Learning Algorithm 81%
• Prediction Model 68%
• Steel 64%
• Prediction Accuracy 61%
• Deviation 56%
• Hierarchical Clustering 47%
• Linear Regression 35%
• Hybrid Method 22%
• Process Variables 22%
• Prediction 13%
• Trade-offs 12%
• Experiment 10%
• Performance 6%
• Industry 6%

Engineering & Materials Science

• Learning algorithms 56%
• Machine learning 49%
• Genetic algorithms 47%
• Steel 39%
• Hierarchical clustering 19%
• Linear regression 17%
• Hot rolling 9%
• Industry 3%
• Experiments 3%