Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the concrete compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy. The best model will be helpful for civil engineers in choosing the appro…
☆23Jul 28, 2020Updated 5 years ago
Alternatives and similar repositories for Concrete-Compressive-Strength-Prediction
Users that are interested in Concrete-Compressive-Strength-Prediction are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Concrete Compressive Strength Prediction using Machine Learning☆27Apr 7, 2020Updated 6 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 3 years ago
- ☆14Oct 26, 2019Updated 6 years ago
- How would you predict the compressive strength of concrete as a function of its constituent materials and curing time? In this portfolio …☆13Nov 27, 2020Updated 5 years ago
- ☆14Jun 17, 2022Updated 4 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Machine Learning-based Second-order Analysis of Beam-columns through Physics-Informed Neural Networks☆16Feb 18, 2025Updated last year
- Predict the wall shear stress along the coronary artery using Deep Learning☆13Aug 9, 2021Updated 4 years ago
- Linear elastic analysis of heterogeneous materials and structures with the Extended Multiscale Finite Element Method (EMsFEM)☆25May 27, 2025Updated last year
- Data corresponding to the paper "Assembly sequence optimization of spatial trusses using graph embedding and reinforcement learning"☆12Dec 29, 2023Updated 2 years ago
- Open source codes for coupling of Finite Element Method and Discrete Element Method using YADE, and OOFEM softwares.☆58Aug 27, 2020Updated 5 years ago
- A novel GNN-LSTM-based fusion model which could accurately predict the seismic responses of multiple structures with different geometry.☆103Apr 22, 2024Updated 2 years ago
- The open virtual platform RC-FIAP, developed in Python, with the analysis library OpenSeesPy at its core, is presented to evaluate the se…☆17Aug 24, 2023Updated 2 years ago
- CU-BEN serial version: geometric and material nonlinear static and transient dynamic structural analysis/ linear acoustic fluid structure…☆11Apr 19, 2020Updated 6 years ago
- This repository contains python codes to classify earthquake rupture based on random forest and neural network.☆15Jun 20, 2019Updated 7 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- 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
- Fast nonlinear FEA tailored for topology optimization☆33Apr 30, 2022Updated 4 years ago
- Basic deep learning models in PyTorch.☆10May 18, 2020Updated 6 years ago
- THe legacy HYPLAS code with multiscale modelling capabilities☆13Jun 13, 2019Updated 7 years ago
- Matlab codes: Comparative study of truss sizing optimisation problem 2020☆10Apr 26, 2020Updated 6 years ago
- The code is for two phase demonstration as example 1 shown in the paper - Gao, Yi, and Yongming Liu. "Reliability-based topology optimiza…☆12Dec 27, 2021Updated 4 years ago
- Bees CNN Algorithm (A Fuzzy Evolutionary Deep Learning)☆10Dec 20, 2024Updated last year
- Simulation kit for Complex Fluid Solid Soil Mechanics☆39Oct 30, 2024Updated last year
- elasto-plastic deformation finite element code☆12Jul 7, 2015Updated 10 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Matlab implementation to solve three-dimensional structural topology optimization problems☆15Feb 28, 2024Updated 2 years ago
- ☆11Oct 6, 2020Updated 5 years ago
- Physics Informed Neural Networks (PINNs) is a machine learning technique that incorporates physical laws and constraints into the neural …☆12Sep 27, 2024Updated last year
- Predicting 2D Steady State Fluid Flow Fields using Convolutional Neural Networks☆12Oct 3, 2020Updated 5 years ago
- A discrete element method (DEM) calibration framework for LIGGGHTS☆12Oct 24, 2019Updated 6 years ago
- User interface for LIGGGHTS that will generate a text file for LIGGGHTS simulations☆14Oct 4, 2017Updated 8 years ago
- Approximate Bayesian Computation in python☆11Feb 19, 2015Updated 11 years ago
- A basic example of using physics informed machine learning for enhanced structural dynamics modeling☆10Jul 7, 2023Updated 2 years ago
- A courseware module that covers the fundamental concepts in probability theory and their implications in data science. Topics include pro…☆11Jun 9, 2026Updated 2 weeks 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.
- Physics-informed neural networks (PINNs)☆15Jun 7, 2022Updated 4 years ago
- Maximum-rectifier-function approach for stress-based topology optimization☆12Sep 22, 2022Updated 3 years ago
- Failure mode identification of shear walls☆18Feb 13, 2020Updated 6 years ago
- virtual element method for space-time dynamic analysis☆15Mar 18, 2025Updated last year
- 🐾 EmotionCube: An intelligent companion robot is designed based on expression recognition and intelligent speech.☆19May 27, 2024Updated 2 years ago
- The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …☆17Jun 18, 2026Updated last week
- ☆10Jun 22, 2026Updated last week