A simple DNN regression for the chemical composition in essential oil

2024/12/17 by Yuki Harada, Shuichi Maeda, Harada, Yuki +5 · 1 citation
Chemical Engineering · Chemistry · #Analytical Chemistry and Chromatography #Chemical and Physical Properties in Aqueous Solutions #FOS: Computer and information sciences #Machine Learning (cs.LG) #Thermodynamic properties of mixtures

paper · pdf · doi:10.48550/arxiv.2412.12936

openalex publication_date 2024/12/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Although experimental design and methodological surveys for mono-molecular activity/property has been extensively investigated, those for chemical composition have received little attention, with the exception of a few prior studies. In this study, we configured three simple DNN regressors to predict essential oil property based on chemical composition. Despite showing overfitting due to the small size of dataset, all models were trained effectively in this study.

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