ericdhitchens / Predicting_Concrete_Compressive_Strength
How would you predict the compressive strength of concrete as a function of its constituent materials and curing time? In this portfolio project, I optimize a model for determining concrete compressive strength using a deep neural network in Tensorflow 2.0 and compare its performance to linear models.
☆10Updated 4 years ago
Alternatives and similar repositories for Predicting_Concrete_Compressive_Strength:
Users that are interested in Predicting_Concrete_Compressive_Strength are comparing it to the libraries listed below
- ☆21Updated 3 months ago
- ☆10Updated 8 years ago
- ☆13Updated 5 years ago
- Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the co…☆20Updated 4 years ago
- High Entropy Alloys (HEAs) are multi-chemical elements alloys with exceptional physical properties. HEAs have sparked the interest in eng…☆8Updated 3 years ago
- Machine learning model for complex concentrated alloys/high entropy alloys using TensorFlow☆14Updated 4 years ago
- A combination of lightweight, high specific strength, and good castability make magnesium alloys a promising engineering material for the…☆10Updated 4 years ago
- Python implementation of domain-invariant partial least squares regression (di-PLS)☆20Updated 2 months ago
- Python scripts for physics-informed neural networks for corrosion-fatigue prognosis☆34Updated 2 years ago
- Concrete Compressive Strength Prediction using Machine Learning☆24Updated 4 years ago
- 基于粒子群算法优化的BPNN和ElM对海浪高度的预测☆40Updated 2 years ago
- Sanitized Grey Wolf Optimizer(SGWO)-Support Vector Regressor (SVR)☆74Updated 2 years ago
- Training Neural Network with Particle Swarm Optimization☆13Updated 6 years ago
- This tutorial was prepared for the BIG-MAP AI school January 2022 by Jonas Busk (jbusk@dtu.dk).☆11Updated 3 years ago
- This repository contains example of keras-tcn on easy way.☆57Updated 4 years ago
- Extreme Learning Machine(ELM): Python code☆39Updated 6 years ago
- Incorporating Inductive Bias into Deep Learning: A Perspective from Automated Visual Inspection in Aircraft Maintenance☆55Updated 4 years ago
- Unofficial implementation of paper “Particle Swarm Optimization for Hyper-Parameter Selection in Deep Neural Networks” using Tensorflow/K…☆30Updated 4 years ago
- Predict corrosion rate using Machine Learning☆14Updated 6 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
- Deep Learning models applied to the analysis of VIS-NIR spectral data☆113Updated 3 months ago
- The objective of the project is to classify steel plates fault into 7 different types. The end goal is to train several machine Learning …☆16Updated 5 years ago
- This project aims to design, develop and implement the training model by using different inputs data. The machine will able to learn the …☆12Updated 4 years ago
- Genetic Algorithm for Neural Network Architecture and Hyperparameter Optimization and Neural Network Weight Optimization with Genetic Alg…☆12Updated 5 years ago
- Physics Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modelling☆23Updated 5 years ago
- A framework for Bayesian model selection (BMS) and Bayesian model Averaging (BMA).☆39Updated last year
- Python implementation of Least Squares Support Vector Machine for classification on CPU (NumPy) and GPU (PyTorch).☆56Updated last year
- Variable Length Genetic Algorithm for hyperparameter optimization of a CNN☆11Updated 4 years ago
- This repository provides a Python3 Library with implementations of the Least-Squares Support Vector Machine (LS-SVM) machine learning mo…☆40Updated 2 years ago