Fuzzy clustering based hierarchical metamodeling for design optimization

Keyphrases

• Cluster-based 100%
• Metamodel 100%
• Highly Nonlinear 100%
• Proposed Methodology 100%
• Design Space 100%
• Design Optimization 100%
• Fuzzy Clustering 100%
• Region of Interest 50%
• Response Surface Methodology 50%
• Metamodeling Technique 50%
• Optimization Problem 50%
• Global Design 50%
• Response Surface 50%
• Small Region 50%
• Unknown Function 50%
• Computational Burden 50%
• Large Design Space 50%
• Kriging Model 50%
• Reducing Subspace 50%
• Nonlinear Constraints 50%
• Engineering Design Problems 50%
• Fuzzy C-means Algorithm 50%
• Design Region 50%
• Design Optimization Problem 50%
• Unknown Systems 50%
• Large Space 50%
• D Optimization 50%
• Camel-back 50%
• Back Problems 50%

Computer Science

• Metamodeling 100%
• Design Optimization 100%
• Optimization Problem 100%
• Fuzzy Clustering 100%
• Design Problem 50%
• Response Surface Methodology 50%
• Response Surface 50%
• Clustering Method 50%
• fuzzy c mean 50%
• Unknown Function 50%
• Research Topic 50%
• Point Sampling 50%

Engineering

• Design Optimization 100%
• Design Space 100%
• Optimisation Problem 66%
• Optimum Design 66%
• Region of Interest 33%
• Kriging Model 33%
• Response Surface 33%
• Response Surface Methodology 33%
• Engineering Design Problem 33%
• Sampling Point 33%