STUDY OF SITE-SPECIFIC EARTHQUAKE GROUND MOTION EVALUATION MODELS USING MACHINE LEARNING CONSIDERING EPICENTRAL DIRECTION AND RESPONSE DURATION TIME

the relationship between using language learning strategies, learners’ optimism, educational status, duration of learning and demotivation

with the growth of more humanistic approaches towards teaching foreign languages, more emphasis has been put on learners’ feelings, emotions and individual differences. one of the issues in teaching and learning english as a foreign language is demotivation. the purpose of this study was to investigate the relationship between the components of language learning strategies, optimism, duration o...

Preliminary Analysis of the Peaks of Strong Earthquake Ground Motion--dependence of Peaks on Earthquake Magnitude, Epicentral Distance, and Recording Site Conditions By

Analyses of peak amplitudes of strong earthquake ground motion have been carried out with the emphasis on their dependence on earthquake magnitude, epicentral distance, and geological conditions at the recording site. Approximate empirical scaling functions have been developed which, for a selected confidence level, yield an estimate of an upper bound of peak accelerations, velocities, and disp...

Influence of Ground Motion Duration on the Structural Response at Multiple Seismic Intensity Levels

This paper aims to investigate the effects of motion duration on the structural seismic demands, seeking potential correlations between motion durations and structural responses at several seismic intensity levels. Three seismic intensity levels with 100years, 475years, and 2475years earthquake return periods (RPs) are first considered for correlation computations. Spectrally matched ground mot...

Dust source mapping using satellite imagery and machine learning models

Predicting dust sources area and determining the affecting factors is necessary in order to prioritize management and practice deal with desertification due to wind erosion in arid areas. Therefore, this study aimed to evaluate the application of three machine learning models (including generalized linear model, artificial neural network, random forest) to predict the vulnerability of dust cent...

Earthquake Ground Motion