2026-10-13T22:58:52Z https://www.scidb.cn/oai

10.57760/sciencedb.j00124.00435 2026-02-10T18:05:26Z

2026-02-10 The original dataset of "Prediction of density and viscosity and identification of key features of biofuel-alcohol blends based on explainable machine learning models" doi:10.57760/sciencedb.j00124.00435 en This database collected a total of 2262 experimental data on the density and viscosity of biodiesel and diesel alcohol mixtures, including temperature, pressure range, number of experimental points, and uncertainty of experimental methods. The density and viscosity experimental methods used were vibration tube method and capillary tube method. After using the Z-score method to clean the experimental data for outliers, the dataset is divided into a training set, a testing set, and a validation set. The validation set is used to monitor early stopping conditions, while the testing set does not participate in model training and validation, and is used as new unknown data for final performance evaluation. biofuel-alcohol blends; density; viscosity; machine learning Jian-an WANG Shi Jiahao Bi shengshan An Qingsong Gao Kehui Cui Junwei EMBARGO https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank