Combining back-propagation and genetic algorithms to train neural networks for start-up time modeling in combined cycle power plants.
Ilaria BertiniMatteo De FeliceStefano PizzutiPublished in: ESANN (2010)
Keyphrases
- wind speed
- back propagation
- power plant
- neural network
- artificial neural networks
- soft computing
- fuzzy logic
- fault diagnosis
- genetic algorithm
- feed forward
- training algorithm
- bp algorithm
- feed forward neural networks
- feedforward neural networks
- hidden layer
- bp neural network
- coal fired
- multilayer perceptron
- trained neural network
- neural nets
- activation function
- connection weights
- rbf network
- pattern recognition
- backpropagation algorithm
- decision support system
- cascade correlation
- radial basis function neural network
- error back propagation
- levenberg marquardt
- bp network
- multi layer neural network
- historical data
- multi layer perceptron
- control system
- radial basis function
- carbon dioxide
- wavelet neural network
- hybrid models
- learning algorithm
- decision making
- multilayer neural network
- multi objective
- simulated annealing
- genetic algorithm ga
- evolutionary computation
- neural network model
- learning rules
- genetic programming
- case based reasoning
- differential evolution
- weight update
- recurrent neural networks
- knowledge base
- network architecture