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An EA Framework to Avoid Premature Convergence in Stochastic Search
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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Dive into the research topics of 'An EA Framework to Avoid Premature Convergence in Stochastic Search'. Together they form a unique fingerprint.
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Keyphrases
Evolutionary Algorithms
100%
Premature Convergence
100%
Algorithm Framework
100%
Stochastic Search
100%
Search Space
66%
Evolutionary Search
66%
Genetic Algorithm
33%
Elitism
33%
Curb
33%
Benchmark Functions
33%
High Complexity
33%
Performance Improvement
33%
Search Process
33%
Convergence Characteristics
33%
Algorithm Implementation
33%
Genetic Operators
33%
Genetic Operation
33%
Real-time Optimization
33%
Brief Analysis
33%
Local Convergence
33%
Local Optimal Solution
33%
Population Diversity
33%
Suboptimal Solutions
33%
Operator Basis
33%
Computer Science
Search Space
100%
Evolutionary Algorithms
100%
Genetic Algorithm
50%
Local Optimal Solution
50%
Optimization Problem
50%
Genetic Operator
50%
Engineering
Search Space
100%
Optimisation Problem
50%
Curbs
50%
Genetic Algorithm
50%