Dataset for the support vector machine and neural network approaches for stiffness modulus prediction of bituminous mixtures under 4-PB tests within Weave-UNISONO 2021 project, NCN project No 2021/03/Y/ST8/00079, and GACR project GA22-04047K

Summary: The two investigated mixtures have different nominal maximum gradation sizes. The first (Mix1) was prepared for binder layers limited to a maximum size of 16 mm, whereas the second (Mix2) was prepared for base layers limited to a maximum size of 22 mm. Mix1 and Mix2 were tested over a temperature range of 0 to 30 °C and a frequency range of 0.1 to 50 Hz. A number of specimen ranging from 3 to 5 was tested for each testing condition, resulting in 99 averaged stiffness modulus values. The dataset was split so that roughly 25% of the available observations (24 experimental observations) comprised the test set, while the remaining observations comprised the training set. The dataset includes: Outcomes of the 4PBT experimental carried out on two types of asphalt concrete: AC16 (Mix1) and AC22 (Mix2) mixtures 01 Stiffness Modulus AC16 and AC22.csv