An Improved Evolutionary Random Neural Networks Based on Particle Swarm Optimization and Input-to-Output Sensitivity.
Qing-Hua LingYuqing SongFei HanHu LuPublished in: ICIC (1) (2017)
Keyphrases
- particle swarm optimization
- neural network
- desired output
- hidden units
- genetic algorithm
- rbf network
- pso algorithm
- input data
- multiple output
- evolutionary strategy
- input variables
- artificial neural networks
- multi objective
- back propagation
- neural network model
- pattern recognition
- hidden layer
- input pattern
- feed forward neural networks
- evolutionary computation
- particle swarm
- particle swarm optimization algorithm
- fuzzy logic
- output layer
- convergence speed
- feed forward
- global optimization
- metaheuristic
- hybrid algorithm
- learning algorithm
- control signals
- connection weights
- evolutionary optimization
- activation function
- multilayer perceptron
- differential evolution
- self organizing maps
- feedforward neural networks
- evolutionary process
- ant colony optimization
- feedback loop
- sufficient conditions
- feature space
- sensitivity analysis
- computational intelligence
- multi layer
- bayes rule
- feature selection