Prediction of stiffness modulus of bituminous mixtures using the applications of multi expression programming and gene expression programming

The database contains a total 360 data points which was developed using data extracted from asphalt laboratories and plant mixtures. These mixes were designed using aggregates (limestone, sharp sand and filler) and asphalt binders (Trinidad Lake Asphalt - TLA and modified binders - MB). The asphalt mixtures are dense-graded hot mix asphalt (HMA) and gap-graded stone matrix asphalt (SMA). The variables in the dataset were chosen based on the requirements of existing dynamic modulus models as well as requirements for quality control and assurance (QC & QA) evaluation of asphalt concrete mixtures. The data was used to develop soft computing models using gene expression programming and multi expression programming techniques.本数据库总计包含360组数据样本，所有数据均提取自沥青实验室与工厂拌制的混合料。本数据集所用的混合料采用集料（石灰石、细砂（sharp sand）及填料）与沥青胶结料（特立尼达湖沥青（Trinidad Lake Asphalt, TLA）及改性胶结料（modified binders, MB））配制而成。该沥青混合料涵盖密级配热拌沥青混合料（HMA）与间断级配碎石沥青混合料（SMA）两种类型。本数据集选取的特征变量既满足现有动态模量模型的参数要求，同时也符合沥青混凝土混合料的质量控制与质量保证（QC&QA）评估需求。本数据集已被用于基于基因表达式编程与多表达式编程技术构建软计算模型。