Dataset for the mechanical performance prediction of asphalt mixtures: a baseline study of linear and non-linear regression compared with Neural Network modelling within Weave-UNISONO 2021 project, NCN project No 2021/03/Y/ST8/00079, and GACR project GA22-04047K

Summary: Two selected mixtures were thoroughly investigated in an experimental trial carried out by means of a four-point bending test (4PBT) apparatus. The mixtures were prepared using aggregate, a conventional 50/70 penetration grade bitumen, and limestone filler. Their stiffness moduli (SM) were determined while samples were exposed to loading frequencies from 0.1 to 50 Hz, and testing temperatures ranged from 0 to 30 °C. The main scope of this research was to compare analysis between different modelling approaches: conventional regressions, both linear and non-linear, and artificial neural networks. The dataset includes: Outcomes of the 4PBT experimental carried out on two types of asphalt concrete: NMAS16 and NMAS22 mixtures Stiffness Modulus NMAS16.csv Stiffness Modulus NMAS22.csv