A5054325288- Seismic Performance and Analysis
- Structural Health Monitoring Techniques
- Structural Engineering and Vibration Analysis
- Masonry and Concrete Structural Analysis
- Seismic Waves and Analysis
- Structural Load-Bearing Analysis
- Anomaly Detection Techniques and Applications
- Seismic Imaging and Inversion Techniques
- Advanced Clustering Algorithms Research
- Remote Sensing and Land Use
- Fluid Dynamics and Vibration Analysis
- Fault Detection and Control Systems
- Infrastructure Maintenance and Monitoring
- Image and Signal Denoising Methods
- Mechanical stress and fatigue analysis
- Structural Response to Dynamic Loads
- Blind Source Separation Techniques
- Landslides and related hazards
- Structural Behavior of Reinforced Concrete
- Remote-Sensing Image Classification
- Machine Fault Diagnosis Techniques
Amirkabir University of Technology
2018-2025
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In this paper, a stochastic-parametric model is developed for simulating the temporal and spectral nonstationary characteristics of ground motion sequences. proposed model, after extracting wavelet coefficients sequence by using complex discrete transform smoothing them Normal kernel function, they are simulated Gaussian mixture distribution. This simulates multiple peaks in time domain, several dominant frequency at each time, relaxation between motions, steps cumulative energy curve...
In this paper, it is aimed to perform clustering analysis on a large set of near-fault ground motions based the intensity velocity pulses. For purpose, pulses these are extracted asymmetric Gaussian chirplet model (AGCM), adapted dictionary-free orthogonal matching pursuit (ADOMP) algorithm, and Newton method. The location first AGCM atom considered as real pulse, its combination with adjacent atoms reconstructs pulse motions. addition, hierarchical k-means used cluster into two, three, five...