censer_dispenser

dsp_filter_noise-

By using digital signal processing to eliminate unpleasing noise. Original sound - Lisa_noise.wav, the processed file - Processed_Lisa.wav.

evolutionary-computation-navigation

🎮OmegaXYZ.com演化计算文章目录（实时更新）

hanoi

game creation

ibea

Indicator-based Evolutionary Algorithm with Epsilon indicator

jmetalpy

A framework for single/multi-objective optimization with metaheuristics

learning-note-advanced-python-

taking notes from codecademy learning

lunarlander

By using genetic algorithm to simulate lunarlander optimization.

mich0611

Config files for my GitHub profile.

moea-d

Q. Zhang and H. Li, MOEA/D: A Multi-objective Evolutionary Algorithm Based on Decomposition, IEEE Trans. on Evolutionary Computation, vol.11, no. 6, pp712-731

nsga-ii

This is a python implementation of NSGA-II algorithm. NSGA is a popular non-domination based genetic algorithm for multi-objective optimization. It is a very effective algorithm but has been generally criticized for its computational complexity, lack of elitism and for choosing the optimal parameter value for sharing parameter σshare. A modified version, NSGA II was developed, which has a better sorting algorithm , incorporates elitism and no sharing parameter needs to be chosen a priori.

nsga-ii-

Nondominated sorting genetic algorithm

nsga2

Implementation NSGA-II algorithm in form of python library

pacman-ai

BFS, DFS, A*, and Uniform Cost Search Algorithms implemented for Pacman game

pymultiobjective

A python library for the following Multiobjective Optimization Algorithms or Many Objectives Optimization Algorithms: C-NSGA II; CTAEA; GrEA; HypE; IBEA-FC; IBEA-HV; MOEA/D; NAEMO; NSGA II; NSGA III; OMOPSO; PAES; RVEA; SMPSO; SMS-EMOA; SPEA2; U-NSGA III

risc_v-assembly

HW assignment of RISC_V

stackingclassifiers_medium

Stacking Classifiers for Higher Predictive Performance

us_medical_insurance_codecademy