P-14　機械学習による高温高圧水に対するバイオマス由来化合物の溶解度推算

DOI

書誌事項

タイトル別名
  • P-14　Estimation of the Solubility of Biomass-derived Organic Compounds in High-temperature and High-pressure Water by Machine Learning

抄録

<p>The estimation of the solubility of biomass-derived organic compounds in high-temperature water is important for designing chemical processes. This study aimed at predicting the solubility of organic compounds in high-temperature water in the range of 100–250 °C using machine learning. The chemical structure of the organic compound was converted into 196 descriptors (parameters) using an open-source toolkit. The experimental solubility data were regressed using the descriptors, temperature, and water density. The regression methods of ordinary least squares (OLS), least absolute shrinkage and selection operator (Lasso), and support vector regression (SVR) were compared. A regression method combining the Lasso and SVR (Lasso + SVR) was developed. The model thus obtained by Lasso + SVR was found to accurately predict the solubility of organic compounds in high-temperature water, with a root-mean-square error of 0.5. The findings in this study would be useful for predicting the solubility of any organic compound in high-temperature water.</p>

収録刊行物

詳細情報 詳細情報について

  • CRID
    1390294407620298496
  • DOI
    10.20550/jiebiomassronbun.18.0_91
  • ISSN
    24238341
    24238333
  • 本文言語コード
    ja
  • データソース種別
    • JaLC
  • 抄録ライセンスフラグ
    使用不可

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