Concrete Compressive Strength Prediction using Machine Learning
☆28Apr 7, 2020Updated 5 years ago
Alternatives and similar repositories for Concrete-compressive-strength
Users that are interested in Concrete-compressive-strength are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆14Oct 26, 2019Updated 6 years ago
- Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the co…☆23Jul 28, 2020Updated 5 years ago
- The aim of this project is to develop a solution using Data science and machine learning to predict the compressive strength of a concret…☆22Jun 25, 2023Updated 2 years ago
- How would you predict the compressive strength of concrete as a function of its constituent materials and curing time? In this portfolio …☆12Nov 27, 2020Updated 5 years ago
- Example of using AWS for serverless on-demand seismic processing.☆14Mar 30, 2021Updated 4 years ago
- DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Classical Carleman solution of the viscous Burgers equation, used in https://arxiv.org/abs/2011.03185.☆12Mar 1, 2021Updated 5 years ago
- Machine Learning-based Second-order Analysis of Beam-columns through Physics-Informed Neural Networks☆15Feb 18, 2025Updated last year
- ☆11Feb 28, 2022Updated 4 years ago
- Predict the wall shear stress along the coronary artery using Deep Learning☆12Aug 9, 2021Updated 4 years ago
- 2D framing / pixel structural optimization (beyondAEC 2018 hackathon project)☆15Jul 28, 2018Updated 7 years ago
- This repository contains python codes to classify earthquake rupture based on random forest and neural network.☆15Jun 20, 2019Updated 6 years ago
- Developing an interpretable machine learning model for predicting the shear strength of RC squat walls using XGBoost and SHAP.☆14Aug 30, 2021Updated 4 years ago
- Implementing ensemble learning methods for shear strength prediction of RC deep beams with/without web reinforcements☆16Mar 10, 2021Updated 5 years ago
- Basic deep learning models in PyTorch.☆10May 18, 2020Updated 5 years ago
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- Getting started with python tutorial repo for Transform2020☆31Jun 8, 2020Updated 5 years ago
- Resources for emu☆18Sep 10, 2024Updated last year
- Physics Informed Neural Networks (PINNs) is a machine learning technique that incorporates physical laws and constraints into the neural …☆12Sep 27, 2024Updated last year
- User interface for LIGGGHTS that will generate a text file for LIGGGHTS simulations☆14Oct 4, 2017Updated 8 years ago
- Molecular dynamics simulations in Python and Cython. Simulates Lennard-Jones particles in the NVE ensemble using the Verlet method and hi…☆12Jun 2, 2015Updated 10 years ago
- The Anansi Hexapod Robot is a 3D-printable hexapod frame based on 24 Dynamixel MX-28 Robot Actuators. The design is radially symmetrical …☆11Sep 29, 2021Updated 4 years ago
- A basic example of using physics informed machine learning for enhanced structural dynamics modeling☆10Jul 7, 2023Updated 2 years ago
- Failure mode identification of shear walls☆18Feb 13, 2020Updated 6 years ago
- Tumor growth modeling toolkit. Tumor growth numerical solvers.☆16Oct 13, 2025Updated 5 months ago
- End-to-end encrypted email - Proton Mail • AdSpecial offer: 40% Off Yearly / 80% Off First Month. All Proton services are open source and independently audited for security.
- 🌌 Applications of Physics-Informed ML: A collection of notebooks from my Masters research, exploring how machine learning can solve scie…☆11Nov 9, 2024Updated last year
- Folder corresponding to 2017 summer project at MD Anderson Cancer Center.☆12Nov 14, 2019Updated 6 years ago
- ☆10Feb 9, 2025Updated last year
- Engineer-Ayesha-Shafique / Brain-Tumor-Segmentation-and-Detection-using-UNET-and-Watershed-in-PythonCreate a precise and efficient method for recognizing and segmenting brain tumours from MRI images. It entails pre-processing MRI images …☆11Jun 9, 2023Updated 2 years ago
- Deep Transfer Learning and Time-Frequency Characteristics-Based Identification Method for Structural Seismic Response☆34Sep 14, 2021Updated 4 years ago
- Crack detection for an autonomous UAV☆13Jul 6, 2018Updated 7 years ago
- ☆15Jun 18, 2024Updated last year
- A novel GNN-LSTM-based fusion model which could accurately predict the seismic responses of multiple structures with different geometry.☆100Apr 22, 2024Updated last year
- ☆11Aug 30, 2023Updated 2 years ago
- End-to-end encrypted cloud storage - Proton Drive • AdSpecial offer: 40% Off Yearly / 80% Off First Month. Protect your most important files, photos, and documents from prying eyes.
- Fast calculation of contact angles in tomography images using deep learning☆16Apr 2, 2024Updated last year
- Code Library for Multi-sphere Particles. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2…☆16May 6, 2021Updated 4 years ago
- Metropolis Monte Carlo particle simulations for statistical mechanics in Python and Cython. Simulates Lennard-Jones particles using a Mar…☆12Jun 2, 2015Updated 10 years ago
- Explainability of Brain Tumour Segmentation Models☆15Mar 24, 2023Updated 3 years ago
- R package for response-surface methodology☆18Mar 24, 2025Updated last year
- Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and hence they have different treatment…☆16Apr 8, 2018Updated 7 years ago
- The purpose of this project is to be able to automatically and efficiently segment and classify high-grade and low-grade gliomas.☆16Feb 27, 2019Updated 7 years ago