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通过对现有数据库管理系统的分析,用Visual C#编写表面活性剂预报数据库的应用程序,建立了可供查询和数据输入的表面活性剂物化参数、分子结构信息以及农药配方数据库。另根据表面活性剂预报数据库中分子结构数据库的功能需要,在此工作的基础上,运用GMA算法,实现表面活性剂二维子结构检索。在预报模块中,运用多元线性回归方法建立了三种定量构效关系模型(QSPR)预报硫酸盐、磺酸盐、聚氧乙烯醚类表面活性剂的临界胶束浓度(CMC)值,以及一种预报硫酸盐类表面活性剂亲水亲油平衡值(HLB)的QSPR模型。
Through the analysis of the existing database management system, using Visual C # to prepare the application program of surfactant forecasting database, the physicochemical parameters, molecular structure information and pesticide formula database of surfactant for query and data input were established. According to the functional requirement of the molecular structure database in the surfactant prediction database, based on this work, the GMA algorithm was used to search the two-dimensional substructure of the surfactant. In the prediction module, three kinds of quantitative structure-activity relationship models (QSPR) were used to predict the critical micelle concentration (CMC) of sulfates, sulfonates and polyoxyethylene ether surfactants by multivariate linear regression method. QSPR Model for Predicting Hydrophilic Lipophilic Balance (HLB) of Sulfate Surfactants.