
Neda Asgarkhani
Employment
- Ph.D. student at Gdasnk university of technology
Keywords Help
- machine learning
- data-driven techniques
- artificial neural networks
- buckling-restrained braced frame machine-learning algorithm residual interstory drift seismic retrofit seismic performance curve seismic failure probability
- computational method - damaged-building - retrofitting of buildings - mainshock-aftershock sequence
- computational method, active learning, ensemble machine-learning mod-el, retrofitting structures, mainshock-aftershock sequence.
- computational optimization
- cross-sectional area
- dome structures, actuators, actuation, optimization, structural control
- dome structures.
Business contact
- Location
- Al. Zwycięstwa 27, 80-219 Gdańsk
- Phone
- +48 58 348 62 62
- biznes@pg.edu.pl
Social media
Publication showcase
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
Many studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
Complexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
High-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the...
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