The natural period of vibration is one of the most significant factors used in the seismic
design of buildings. Although the building design codes and previous studies provide some …

In this study, we used four different machine learning models-artificial neural network (ANN),
support vector regression (SVR), k-nearest neighbor (KNN), and random forest (RF)-to …

Abstract Machine learning has become a powerful tool in structural and earthquake
engineering to accurately predict structural design parameters; however, these complex …

In this work, the estimation of the fundamental period of vibration of masonry infilled RC
frame structures is achieved using both Machine Learning techniques and concise …

The fundamental period (T FP) of vibration is the time required for a structure to complete
one full cycle of vibration, and it is one of the main features of the structural system. It highly …

The precise prediction of the fundamental vibrational period for reinforced concrete (RC)
buildings with infilled walls is essential for structural design, especially earthquake-resistant …

Fundamental period of vibration of a structure is an important parameter which goes in the
seismic analysis and design. There are limitations in applying analytical or semi-empirical …

Predicting the structure's fundamental period is a challenging task since its value changes
when the features of buildings change. However, it is more cumbersome for reinforced …

One of the most important parameters used in the frame design process is the fundamental
period. Numerous relationships are provided in the regulations and articles to determine the …

The aim of this study is to develop a machine learning network to estimate the fundamental
vibration period values of existing reinforced concrete (RC) buildings with damaged …