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- W1551803855 abstract "Nonlinear system behavior is not always well characterized by linearized system models, especially if the system is chaotic. This research studies the use of a neural network algorithm structure to model two nonlinear systems, a quadratic system and a chaotic system. An evolutionary programming approach is employed to train the neural nets so that the training process might better avoid selecting weighting parameters that represent a local minimum rather than a global minimum. This training approach is compared with the more standard backpropagation technique. >" @default.
- W1551803855 created "2016-06-24" @default.
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- W1551803855 date "2002-12-17" @default.
- W1551803855 modified "2023-10-16" @default.
- W1551803855 title "Identifying nonlinear dynamic systems using neural nets and evolutionary programming" @default.
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- W1551803855 doi "https://doi.org/10.1109/acssc.1994.471588" @default.
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