Bio-Inspired Genetic Algorithms with Formalized Crossover Operators for Robotic Applications.
Jie ZhangMan KangXiaojuan LiGeng-yang LiuPublished in: Frontiers Neurorobotics (2017)
Keyphrases
- bio inspired
- crossover operator
- genetic algorithm
- mutation operator
- evolutionary algorithm
- swarm intelligence
- fitness function
- genetic operators
- artificial neural networks
- memetic algorithm
- crossover and mutation operators
- modular neural networks
- genetic algorithm ga
- explore the search space
- differential evolution
- traveling salesman problem
- hybrid intelligent systems
- multi objective
- population diversity
- particle swarm optimization
- simulated annealing
- ant colony optimization
- evolutionary computation
- genetic programming
- neural network
- selection operator
- nsga ii
- low level image processing
- metaheuristic
- fuzzy logic
- neural models
- data mining
- particle swarm optimization pso
- tabu search
- optimization problems
- crossover and mutation
- genetic search
- cost function
- machine learning
- mutation probability
- biological inspired