OtterMars

springboot-

基于 Java SpringBoot 的项目初始模板，整合了常用框架和主流业务的示例代码。 只需 1 分钟即可完成内容网站的后端！！！大家还可以在此基础上快速开发自己的项目。

java_shop

Java商城管理系统，基于java+springboot+vue开发的电子商城网站 - 毕业设计 - 课程设计

awesome-chatgpt-prompts-zh

ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。

Whale-optimization-algorithm-with-a-modified-mutualism-phase

S. Chakraborty, A. Kumar Saha, S. Sharma, S. Mirjalili and R. Chakraborty, "A novel enhanced whale optimization algorithm for global optimization", Computers & Industrial Engineering, vol. 153, p. 107086, 2021

improved-WOA-based-on-nonlinear-adaptive-weight-and-golden-sine-operator

J. Zhang and J. Wang, "Improved Whale Optimization Algorithm Based on Nonlinear Adaptive Weight and Golden Sine Operator", IEEE Access, vol. 8, pp. 77013-77048, 2020.

pyMetaheuristic

pyMetaheuristic: A Comprehensive Python Library for Optimization

AltWOA

Altruistic Whale Optimization Algorithm (AltWOA)

swarmlib

This repository implements several swarm optimization algorithms and visualizes them. Implemented algorithms: Particle Swarm Optimization (PSO), Firefly Algorithm (FA), Cuckoo Search (CS), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA)

Broad-Learning-System

BroadLearningSystem

here is the introduce of bls

Steel-Properties-Prediction-using-ML

Project_Prediction_of_Failure_in_Steel_Frame

STAT 451: Machine Learning at UW-Madison (Fall 2020)

Mechanical-properties-of-alloy-Regression-Problem

Prediction of mechanical Properties of low-steel alloy using regression models

Steel-Annealing-class-prediction-through-decision-tree

Project_LASSO

Use lasso to select a descriptor for predicting the abrasion resistance of steels

JSW_Internship

Property Prediction model using regression algorithms , this project is the part of my summer internship at JSW steel 2021 We were provided with raw data of 5135 rows and 45 columns which had to be cleaned first and later applied 5 different algorithms like KNN, Random Forest, ANN, Support Vector Regressor and Multiple Regressor to predict which gave the highest R2_score value and the least RMSE. Conclusion :- Random Forest was found to be relatively the best learner for this model and hence we deployed our machine learning model using html, css, flask.

Estimate-Mechanical-Properties-of-Steel-compostions

This repository contains the code for predicting the Mechanical Properties of steels given its composition.

Steel-Grade-Classification

steel_parameters

Steel-Project

Project_ArcelorMittal

STEEL-PROJECT

pythonProjects

SFE

This repository is the supplemental data and code for the journal paper "A Data-driven Machine Learning approach to predicting Stacking Fault Energy in Austenitic Steels".

Steel-Properties-Prediction

Prediction of steel properties

Steel-Plates-fault-diagnosis-using-Classification-Models

The objective of the project is to classify steel plates fault into 7 different types. The end goal is to train several machine Learning Algorithms for automatic pattern recognition.

rvfln

A Python implementation of random vector functional networks and broad learning systems using Sklearn's Regressor and classifier APIs

Broad-Learning-System

BLS Code

Improved-B-RVFL-nets

This project presents a complete Bayesian framework combined with the Random vector function-link nets (RVFL) algorithm for complicated data modeling, where we add the prior distribution both on the combination weights and the parameters of the basic functions.

Tensorflow_LinearRegression

Example of Linear regression using Tensorflow with GOT DataSet

modnet

MODNet: a framework for machine learning materials properties

matbench

Matbench: Benchmarks for materials science property prediction