Information Directed Sampling for Combinatorial Material Synthesis and Library Design

この論文にアクセスする

この論文をさがす

著者

抄録

Combinatorial techniques have become more and more important in many areas of chemistry and chemical engineering research. It was suggested that simulated annealing can be used to improve the efficiency of sampling in combinatorial methods. However, without priori model estimates of fitness function, true importance sampling cannot be performed. In this case, the efficiency of annealing is only as good as random search. We suggested that a simple prediction model using currently available data can be constructed using a generalized regression neural network. An index of our uncertainty about a point in the search space can also be established using information entropy. An information free energy combined the two indices to direct the search so that importance sampling is performed. Two benchmark problems were used to model the optimization problem involved in combinatorial synthesis and library design. We showed that when importance sampling is performed, the combinatorial technique became much more effective. The improvement in efficiency over undirected methods is especially significant when the size of the problem becomes very large.

収録刊行物

  • Journal of chemical engineering of Japan

    Journal of chemical engineering of Japan 36(9), 1034-1044, 2003-09-01

    公益社団法人 化学工学会

参考文献:  35件中 1-35件 を表示

各種コード

  • NII論文ID(NAID)
    10013414318
  • NII書誌ID(NCID)
    AA00709658
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    00219592
  • NDL 記事登録ID
    6730816
  • NDL 雑誌分類
    ZP1(科学技術--化学・化学工業)
  • NDL 請求記号
    Z53-R395
  • データ提供元
    CJP書誌  NDL  J-STAGE 
ページトップへ