Linear vs. Symbolic Regression for Adaptive Parameter Setting in Manufacturing Processes

Keyphrases

• Manufacturing Process 100%
• Symbolic Regression 100%
• Parameter Adaptation 100%
• Parameter Setting 66%
• Manufacturing Firms 33%
• Product Quality 33%
• Machine Learning Techniques 33%
• Parameter Dependence 33%
• Process Quality 33%
• Scrap 33%
• Trial-and-error 33%
• Multiple Models 33%
• Rule-based 33%
• Quality Level 33%
• Parameter Selection 33%
• High-skilled Labor 33%
• Production Conditions 33%
• Critical Process Parameters 33%
• Real-time Adjustment 33%
• Linear Regression Method 33%
• Competitive Behavior 33%
• Individual Property 33%
• Parameter Estimation Model 33%
• Settings Approach 33%

Computer Science

• Adaptive Parameter 100%
• Regression Method 50%
• Domain Knowledge 50%
• Parameter Estimation 50%
• Collected Data 50%
• Product Quality 50%
• Critical Process 50%
• Process Quality 50%
• Machine Learning 50%
• Learning System 50%

Engineering

• Manufacturing Process 100%
• Symbolics 100%
• Applicability 33%
• Process Parameter 33%
• Parameter Estimation 33%
• Machine Learning Method 33%
• Manufacturing Company 33%
• Collected Data 33%
• Domain Knowledge 33%
• Quality Level 33%
• Individual Property 33%