Identifying Tobacco Control Policy Drivers: A Neural Network Approach.
Xiaojiang DingSusan E. BedingfieldChung-Hsing YehRon BorlandDavid YoungSonja Petrovic-LazarevicKen CoghillPublished in: ICONIP (2) (2009)
Keyphrases
- control policy
- neural network
- long run
- approximate dynamic programming
- control policies
- reinforcement learning
- admission control
- back propagation
- neural network model
- pattern recognition
- artificial neural networks
- radial basis function
- recurrent neural networks
- batch mode
- fault diagnosis
- genetic algorithm
- key factors
- infinite horizon
- neural network is trained
- bp neural network
- associative memory
- feed forward
- optimal policy
- fuzzy logic
- lower bound
- objective function
- machine learning