.... Advanced analytics and machine learning allow for the identification of patterns in historical data, leading to more accurate forecasts and better-informed maintenance planning. In civil engineering, this approach is particularly relevant for managing complex assets such as bridge structures. This article...

... indicator for assessing the bonding performance. In this study, interpretable machine learning (ML) methods were used to analyse the effects of different parameters on interface shear strength. A database consisting of 305 UHPC–NC shear tests was created, and the isolation forest algorithm was applied...

...Hoang Ha, PhD; Le Van Manh, PhD; Dam Duc Nguyen, MEng; Mahdis Amiri, PhD; Indra Prakash, PhD; Binh Thai Pham, PhD A novel hybrid model, based on machine learning technique, for quick and accurate prediction of the vertical deflection of steel–concrete composite bridges was developed. The model...

...Kumar Rajnish, BTech, MTech; Anoop Kodakkal, BTech, MTech; Daniel H. Zelleke, BSc, MTech; Rishith E. Meethal, BTech, MSc; Vasant A. Matsagar, BE, ME, PhD; Kai-Uwe Bletzinger, Dr-Ing; Roland Wüchner, Dr-Ing The implementation of machine learning for the real-time prediction of the suitable value...

..., digital twins, computer vision, machine learning and deep learning are now integrated parts of the new-generation of BHM operations. This paper presents a brief overview of these latest BHM technologies. A relatively new technological approach is bridge health monitoring (BHM), which is implemented...