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A simple DNN regression for the chemical composition in essential oil

arXiv 2412.12936 ↗First posted 17 Dec 2024cs.LGcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 20 references that are in the map. First posted on arXiv 17 Dec 2024.

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4 of 20 references.

References · 4

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  2. 2017Graph Attention Networkscited by 8,923
  3. 2015A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classificationcited by 92
  4. 2023Olfactory Label Prediction on Aroma-Chemical Pairscited by 2

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  1. 2025Motional representation; the ability to predict odor characters using molecular vibrationscited by 0