An Active Search Method for Finding Objects with Near-Optimal Property Values within a Given Set

Journal of the Brazilian Chemical Society

Matta, Cláudia E. da¹  Soares, Sófacles F. C.¹  Instituto Federal do Espírito Santo, Serra, Brazil¹  Mectron Engenharia, Indústria e Comércio, São José dos Campos, Brazil¹  Araújo, Mário C. U.¹  Paiva, Henrique M.¹  Galvão, Roberto K. H.¹  Pinto, Luiz A.¹  Instituto Tecnológico de Aeronáutica, São José dos Campos, Brazil¹  Universidade Federal de Itajubá, Itajubá, Brazil¹  Universidade Federal da Paraíba, João Pessoa, Brazil¹  Weber, Karen C.¹ 

关键词:  optimization;    quantitative structure-activity relationship;    antidepressant compounds;    near-infrared spectrometry;    eucalyptus pulp yield;   

DOI  :  10.5935/0103-5053.20160014

学科分类：化学（综合）

来源: SciELO

【 摘 要 】

This paper proposes an active search method aimed at finding objects with optimal or near-optimal y-property values, on the basis of x-variables obtained by indirect, less costly methods. The proposed method progresses in a sequential manner, starting from a small subset of objects with known y-values. At each iteration, the K-nearest neighbour regression technique is employed to obtain estimates Å· for the objects with unknown y-values. The object with best Å· value is then subjected to a direct analysis procedure for evaluation of the y-property. Examples are presented with simulated data, as well as actual quantitative structure-activity relationship (QSAR) and near-infrared (NIR) spectrometry datasets. The QSAR and NIR case studies involve the search for maximal antidepressant activity in a set of arylpiperazine compounds and maximal pulp yield in a set of eucalyptus wood samples, respectively. In all these cases, the active search yielded results closer to the maximal y-value compared to the classical Kennard-Stone algorithm for object selection.

【 授权许可】

Unknown