Machine learning (ML) has evolved rapidly over recent years with the promise to
substantially alter and enhance the role of data science in a variety of disciplines. Compared …

Recent estimates hypothesize that the US will need $1.6 trillion dollars for the rehabilitation,
replacement, and maintenance of existing infrastructure systems within the next 20 years …

Non‐parametric system identification has been widely applied in structural health monitoring
and damage detection based on measured response data. However, the presence of noise …

In a companion paper, a new non‐linear control model was presented for active control of
three‐dimensional (3D) building structures including geometrical and material non …

A new non‐linear control model is presented for active control of three‐dimensional (3D)
building structures. Both geometrical and material non‐linearities are included in the …

Recently, Ghaboussi and Joghataie presented a structural control method using neural
networks, in which a neurocontroller was developed and applied for linear structural control …

This paper presents a dynamic fuzzy stochastic neural network model for nonparametric
system identification using ambient vibration data. The model is developed to handle two …

This paper introduces a new robust neural network methodology for vibration mitigation of
tall building under wind excitation. The building considered is a 76‐storey 306 m concrete …

Compared to the semi-active control and passive control systems, an active control system is
able to achieve the most desirable vibration control performance because of its high …

The neuro‐controller training algorithm based on cost function is applied to a multi‐degree‐
of‐freedom system; and a sensitivity evaluation algorithm replacing the emulator neural …