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- W2000236342 abstract "In this contribution, a Genetic Programming (GP) algorithm is used to develop empirical models of chemical process systems. GP performs symbolic regression, determining both the structure and the complexity of a model. Initially, steady-state model development using a GP algorithm is considered, next the methodology is extended to the development of dynamic input-output models. The usefulness of the technique is demonstrated by the development of inferential estimation models for two typical processes: a vacuum distillation column and a twin screw cooking extruder." @default.
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- W2000236342 date "1997-05-01" @default.
- W2000236342 modified "2023-10-16" @default.
- W2000236342 title "Systems modelling using genetic programming" @default.
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- W2000236342 doi "https://doi.org/10.1016/s0098-1354(97)87659-4" @default.
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