Kinetic modelling: Regression and validation stages, a compulsory tandem for kinetic model assessment
نویسندگان
چکیده
The development of robust and reliable kinetic models is vital to build safe, eco-friendly, cost-competitive chemical processes. Establishing for complex systems such as biomass valorization cumbersome because the modeller must test different fit several experimental observables (or concentrations). Usually, in reaction engineering, model assessment based solely on regression stage outputs. implementation a validation can aid choosing most models, essentially case systems. We studied solvolysis 5-hydroxymethylfurfural (5-HMF) butyl levulinate (BL) constituting consecutive parallel steps. From an existing model, we created 60 synthetic runs batch conditions. In first part, tested four with 5 degrees noise, carried out modelling runs. second two types holdout methods were evaluated. last cross-validation, namely k-fold method, was used. found that 10-fold method allowed more efficient selection results even when noise level high. Besides, allows not scarifying selecting model.
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ژورنال
عنوان ژورنال: Canadian Journal of Chemical Engineering
سال: 2023
ISSN: ['0008-4034', '1939-019X']
DOI: https://doi.org/10.1002/cjce.24956