BILSTM，GRU，LSTM

2DOF model updating problem considering uncertainty including implementations of TMCMC, MCGO and meta-MCGO

Neuro Fuzzy Models using Metaheuristic Algorithms for Short Term Wind Speed Forecasting

Modeling and visualizing the wind force loads on high-rise structures from data collected in wind tunnel experiments.

Dynamics of Mechanical Systems Course Project - PoliMI. Analysis of a truss bridge. Author: Russo Alessio

Translate PDF, EPub, webpage, metadata, annotations, notes to the target language. Support 20+ translate services.

Using Machine Learning to eliminate temperature variability in SHM applications

🔠Foreign language reading and translation assistant based on copy and translate.

Application of LSTM network for Structural Health Monitoring & Non-Destructive Testing

My solutions for Statistics 5065 at Cornell University

Structural damage detection using convolutional neural networks

ML algorithms on synthetically generated input data set for demonstration of my work in SHM

This content shows how to implement time series models provided by Deep Learning Toolbox and Econometrics Toolbox on Simulink model and to update them and forecast value at next time step recursively.

Smartphone based Structural Health Monitoring (SHM)

Pattern Recognition using sensor data and Machine Learning.

Wind speed prediction using machine learning algorithms and time-series models

🌏🌍🌎Translators🌎🌍🌏 is a library that aims to bring free, multiple, enjoyable translations to individuals and students in Python. Translators是一个旨在用Python为个人和学生带来免费、多样、愉快翻译的库。

Matlab Toolbox for uncertainty analysis, sensitivity analysis, parameter estimation, and confidence subcontour box estimation for Mathematical models implemented with Symbolic Math Toolbox or Simulink

Matlab Toolbox for Bayesian Estimation

Averaging noisy data into bins

MATLAB toolbox for performing modal analysis using experimental data

Bayesian optimization of automotive car body designs

Spectral proper orthogonal decomposition in Matlab

Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in noise signals. Hu, K. et al (2001). "Effect of trends on detrended f…

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