LaxmiChaudhary / Modeling-of-strength-of-high-performance-concrete-using-Machine-Learning
☆13Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for Modeling-of-strength-of-high-performance-concrete-using-Machine-Learning
- Concrete Compressive Strength Prediction using Machine Learning☆23Updated 4 years ago
- Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the co…☆19Updated 4 years ago
- Using deep learning techniques like 1D and 2D CNNs, LSTM to detect damage in a structure with hinges/joints after an earthquake.☆13Updated 3 years ago
- Deep LSTM for highly nonlinear system modeling☆50Updated 5 years ago
- How would you predict the compressive strength of concrete as a function of its constituent materials and curing time? In this portfolio …☆10Updated 3 years ago
- Failure mode identification of shear walls☆16Updated 4 years ago
- ☆9Updated 3 years ago
- Earthquake Responses prediction using Deep learning and Database☆35Updated 9 months ago
- A Python class for Reliability analysis including Monte Carlo and FORM methods☆13Updated 3 months ago
- Python scripts for physics-informed neural networks for corrosion-fatigue prognosis☆29Updated 2 years ago
- Deep Transfer Learning and Time-Frequency Characteristics-Based Identification Method for Structural Seismic Response☆26Updated 3 years ago
- xaviergoby / ConvLSTM-Computer-Vision-for-Structural-Health-Monitoring-SHM-and-NonDestructive-Testing-NDTApplication of LSTM network for Structural Health Monitoring & Non-Destructive Testing☆35Updated 3 years ago
- Introduction to Vibration Theory☆32Updated 4 months ago
- CONCEPT is a dataset of lamb-wave measured in composite structures in healthy and damaged states. This experiment was conducted at the SH…☆24Updated 4 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆47Updated 3 years ago
- This GitHub package provides example MATLAB code for finite element model updating. The code offers selection of different updating formu…☆33Updated 2 years ago
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆28Updated last week
- Incorporating Inductive Bias into Deep Learning: A Perspective from Automated Visual Inspection in Aircraft Maintenance☆54Updated 4 years ago
- Physics-informed neural network for fatigue crack propagation (Paris' law)☆11Updated 2 years ago
- Physics-guided Convolutional Neural Network☆59Updated 4 years ago
- Implementing ensemble learning methods for shear strength prediction of RC deep beams with/without web reinforcements☆16Updated 3 years ago
- In this repository, we present an Semantic Segmentation code, based on U-net architecture, that is used for the topographic characterizat…☆15Updated 3 years ago
- We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.☆56Updated last year
- A toolbox for Sequential Bayesian Inference in uncertain nonlinear dynamic systems.☆10Updated 6 months ago
- Python script for automation of parametric study in ANSYS Workbench☆14Updated 5 years ago
- MeltpoolNet: Melt pool Characteristic Prediction in Metal Additive Manufacturing Using Machine Learning☆23Updated 2 years ago
- Bayesian Deep Learning and Deep Reinforcement Learning for Object Shape Error Response and Correction of Manufacturing Systems☆42Updated last year
- Physics-Informed and Hybrid Machine Learning in Additive Manufacturing: Application to Fused Filament Fabrication☆15Updated 2 years ago
- Recursive long short-term memory network for predicting nonlinear structural seismic response☆15Updated 2 years ago
- Demonstration of Particle Swarm Optimization as a training algorithm for Keras neural network models as a gradient-free training alternat…☆34Updated 5 years ago