Bayesian optimization has emerged at the forefront of expensive black-box optimization due
to its data efficiency. Recent years have witnessed a proliferation of studies on the …

Bayesian optimisation is a statistical method that efficiently models and optimises expensive
“black-box” functions. This review considers the application of Bayesian optimisation to …

Wind is an important source of renewable energy, often used to provide clean electricity to
remote areas. For optimal extraction of this energy source, there is a need for an accurate …

In view of the universal existence of multi-source uncertainty factors in engineering
structures, a novel method of dynamic force reconstruction is investigated based on Artificial …

The design of chemical-based products and functional materials is vital to modern
technologies, yet remains expensive and slow. Artificial intelligence and machine learning …

In view of the serious accidents caused by the fatigue operation of tower crane drivers in
construction, this study puts forward a novel type of portable semi-dry electrode to detect the …

The design of materials and identification of optimal processing parameters constitute a
complex and challenging task, necessitating efficient utilization of available data. Bayesian …

Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

To improve machining accuracy of complex parts, a self learning-empowered thermal error
control method of precision machine tools is presented based on digital twin. The memory of …

The concrete mix proportion design process is complex but important, especially in cold,
ocean, underground and other complex engineering environments. In this study, a hybrid …