This study investigates the feasibility of using combination of present ground motion
parameters to have a hybrid parameter that is more correlated with damage. Since RC …

In this study, a genetic algorithm with global searching capability was incorporated into a
neural network calculating process to obtain a highly reliable model for predicting peak …

Despite technological advances in seismic instrumentation, the assessment of the intensity
of an earthquake using an observational scale as given, for example, by the modified …

Comparisons between peak ground motions (PGM s) and intensities are mainly based on
the regression of felt intensity with peak ground acceleration (PGA), peak ground velocity …

This paper presents the development of a non-parametric forecast model based on artificial
neural networks for the direct assessment of Arias Intensity corresponding to a historic …

Examining the effect of strong ground motions on civil engineering structures is important as
it concerns public safety. The present study initially selects twenty‐one bridges with lengths …

This study proposes an improved computational neural network model that uses three
seismic parameters (ie, local magnitude, epicentral distance, and epicenter depth) and two …

Seismic intensity can simply reflect the extent and distribution of earthquake's impact and
damage. A comprehensive and detailed assessment of intensity requires a long time and a …

El objetivo principal de este trabajo fue estudiar teórica y experimentalmente aquellos
procedimientos que permitan limpiar de arsénico un concentrado de cobre, mediante una …

In this paper we suggest the use of diffusion-neural-networks,(neural networks with intrinsic
fuzzy logic abilities) to assess the relationship between isoseismal area and earthquake …