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Superposition of artificial experimental error onto calculated time series: Construction of in-silico data sets

The data and complementary information presented here are related to the research in the article of “https://doi.org/10.1016/j.cej.2018.01.027; Chem. Eng. J., 342, 41–51 (2018)”, where sets of in-silico data are constructed to show a novel method for parameter estimation in biodiesel production from...

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Detalles Bibliográficos
Autores principales: Heynderickx, Philippe M., Roelant, Raf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6100261/
https://www.ncbi.nlm.nih.gov/pubmed/30131967
http://dx.doi.org/10.1016/j.dib.2018.05.073
Descripción
Sumario:The data and complementary information presented here are related to the research in the article of “https://doi.org/10.1016/j.cej.2018.01.027; Chem. Eng. J., 342, 41–51 (2018)”, where sets of in-silico data are constructed to show a novel method for parameter estimation in biodiesel production from triglycerides (Heynderickx et al., 2018) [1]. In this paper, the method for the used error superposition is explained and in order to ensure a ready reproduction by the reader, this work presents the basic steps for superposition of a normally distributed error via a simple Excel® datasheet file.