Name: Shuhua Gao
Type: User
Company: National University of Singapore
Bio: PhD in Control, Intelligent Systems & Robotics. Interested in machine learning, computational intelligence, learning-based control theory and its applications.
Location: Singapore
Blog: https://www.researchgate.net/profile/Shuhua_Gao2
Shuhua Gao's Projects
Optimal Control of Boolean Control Networks with Discounted Cost: An Efficient Approach based on Deterministic Markov Decision Process
Robust Controllability of Boolean Control Networks with Dynamic Programming
Code and materials for "Optimal Robust Set Stabilization of Boolean Control Networks"
Code and other materials accompanying the paper "Set Invariance and Optimal Set Stabilization of Boolean Control Networks: A Graphical Approach"
Boolean Expressions
Advanced WPF Binding which supports expressions in Path property and other features
CGP to evolve Boolean networks
Differential evolution in Julia.
强化学习中文教程(蘑菇书),在线阅读地址:https://datawhalechina.github.io/easy-rl/
Optimization for EV charging.
Evolutionary & genetic algorithms for Julia
Repository of best practices for deep learning in Julia, inspired by fastai
Finite-Horizon Optimal Control of Boolean Control Networks: A Unified Graph-Theoretical Approach
Code for "Master Blazor: Build Inventory Management System in .NET 8" with Fluent UI
Reconstruct Boolean network from data using GA on its DNF
A framework for gene expression programming (an evolutionary algorithm) in Python
Flappy Bird AI using Cartesian Genetic Programming (Evolutionary Computation)
Code for "A Hybrid Approach for Home Energy Management with Imitation Learning and Online Optimization"
Julia and C# interoperation
Embed Julia in .NET programs
Abstractions for Julia Machine Learning Packages
A practice of machine learning algorithms
Please do not feed the models
Minimum-Time Control of Boolean Control Networks
C++ 11 implementation of neural networks for nonlinear system modeling and control with multiple NARMA-L2 models
A short tutorial about how to use unsafe code in P/Invoke.
Highly efficient photovoltaic parameter estimation using parallel particle swarm optimization on a GPU
Python and Julia in harmony.
A reinforcement learning package for Julia
Code for the paper: Rethinking solar photovoltaic parameter estimation: global optimality analysis and a simple efficient differential evolution method