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Meta Model Based EA for Complex Optimization
Maumita Bhattacharya
Data Science and Engineering Research Unit
Machine Vision and Digital Health (MaViDH) Research Group
Cyber Security Research Group (CSRG)
Computing, Mathematics and Engineering
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Keyphrases
Metamodel
100%
Complex Optimization
100%
Evolutionary Algorithms
42%
Function Evaluation
42%
Hybrid EA
42%
Fitness Evaluation
28%
Learning Approaches
14%
Underlying Assumptions
14%
Benchmark Functions
14%
Algorithm Framework
14%
Real-time Optimization
14%
Stochastic Search
14%
Population-based
14%
Function Approximation
14%
Approximate Model
14%
Multiple Models
14%
Uniform Model
14%
Global Minimizer
14%
Fitness Function
14%
Model Dynamics
14%
Modeling Tools
14%
EA Model
14%
Problem Domain
14%
Multimodal Problems
14%
Support Vector Machine
14%
Controlled Use
14%
Noisy Function
14%
Noisy Fitness
14%
Computation Time
14%
Least Squares Support Vector Regression (LSSVR)
14%
Order of Magnitude
14%
Evolutionary Optimization
14%
Model-based Learning
14%
Training Samples
14%
Attractive Alternatives
14%
Uncertain Scenarios
14%
Computer Science
Function Evaluation
100%
Fitness Function
80%
Evolutionary Algorithms
60%
Actual Function
40%
Support Vector Machine
40%
Underlying Assumption
20%
Optimization Problem
20%
Search Technique
20%
Benchmark Function
20%
Approximation (Algorithm)
20%
evolutionary optimization
20%
Learning Approach
20%
Computation Time
20%
Training Sample
20%
Problem Domain
20%