Radial basis function neural network as predictive process control model
1995
This is an experimental study to compare the performance of the widespread backpropagation network (BP) to the performance of a radial basis function (RBF) and a generalized regression neural network (GRNN) for potential use as on-line process models. Criteria for network comparison include generalization ability to unseen data, robustness to process shifts, performance with sparse training data, and computational demands.
Keywords:
- Types of artificial neural networks
- Feedforward neural network
- Time delay neural network
- Physical neural network
- Computer science
- Radial basis function network
- Machine learning
- Multilayer perceptron
- Probabilistic neural network
- Artificial intelligence
- Activation function
- Artificial neural network
- Recurrent neural network
- Backpropagation
- Correction
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