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- W2010816330 abstract "Neural networks are applied to the problem of parameter estimation for process systems. Neural network parameter estimators for a given parametrized model structure can be developed by supervised learning. Training examples can be dynamically generated by using a process simulation, resulting in trained networks that are capable of high generalization. This approach can be used for a variety of parameter estimation applications. A proof-of-concept open-loop delay estimator is described, and extensive simulation results are detailed. Some results of other parameter estimation networks are also given. Extensions to recursive and closed-loop identification and application to higher-order processes are discussed." @default.
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- W2010816330 date "1992-10-01" @default.
- W2010816330 modified "2023-09-26" @default.
- W2010816330 title "Parameter estimation for process control with neural networks" @default.
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- W2010816330 doi "https://doi.org/10.1016/0888-613x(92)90008-n" @default.
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