赵亚楠's starred repositories
Twin-Delayed-DDPG-Model-for-Virtual-AI-motion-
This repo is an implementation of an AI model for virtual motion i.e., humanoid using Twin-Delayed DDPG, which combines state of the art techniques in Artificial Intelligence including continuous Double Deep Q-Learning, Policy Gradient, and Actor Critic implemented using Pytorch
digital-twin
Generate 3D models of your surrounding from photos. Let the world experience your reality.
Twinkle-Exocomet-Model
A modelling tool for exocomet transit observations with Twinkle.
Traffic-Flow-Model
A digital twin of traffic conditions
Simscape-Triplex-Pump
Predictive maintenance algorithm developed using digital twin of hydraulic pump modeled in Simscape
satellite-tracker
Javascript 3D satellite tracker library with up-to-date data from CELESTRAK. Uses Three.js, React and satellite.js for orbit prediction.
plantery-machine-learning-predictor
Hobby project to look at NASA space telescopic images to classify if a celestial object is a planet. Use different ML models, finetuning parameters, feature optimization, and finding the best model for prediction.
Planet-Predictions
Testing machine learning models to classify and predict potential planet data from NASA Kepler telescope with deep learning, support vector machine and logistic regression.
NASA-API-satellite-prediction
Small project that utilizes NASA API to predict next time satellite wil fly over a location and take a picture
NASA-Predictive-Analysis
I created 2 models (SVC and Neural Networks with Keras) to examine the data that NASA collects to find hidden planets outside of our solar system.
aerosol-depth-prediction
Multiple instance regression of aerosol optical depth based on NASA's multispectral imaging data.
Meteorite-Landing
A project that uses Python and NASA data to predict year of landing of meteorites.
Exoplanet-Exploration
Machine learning models using Scikit-Learn capable of classifying candidate exoplanets from a NASA exoplanet dataset.
MYNH-CLEANER---Mapping-Space-Trash-in-real-Time--NASA-Space-Apps-2021
Did you know that we are at significant risk of ending all means of communication and shutting ourselves off from space? In our space there are 36500 objects greater than 10 cm, 1000000 objects from 1 cm to 10 cm and 330 million objects from 1 mm to 1 cm. The space is filled with trash pieces from the missions dispatched, and these pieces only collide to create more trash triggering a never-ending chain of space debris growth. But we have the solution, an interactive web application that provides real time location and predictions of them in real time in an interactive map providing information such as (geospatial, velocity, type, date, time) not only that but the app can predict crashing.
satellite-orbit-prediction
Predicting the position of satellites is one of the big challenges in astronomy. More than 500,000 pieces of debris are tracked as they orbit the Earth. They all travel at speeds up to 28163.52 km/hour, fast enough for a relatively small piece of orbital debris to damage a satellite. If space debris hits the satellite it would result in the creation of more debris. According to NASA, there are more than 3,000 satellites currently revolving around the earth’s orbit. If most of these satellites are damaged as a result of space junk, it will result in the creation of more space debris that will lead to Kessler syndrome. The existing SGP4-simulator in the satellite predicts the position of the satellite before but it’s an approximation. The solution can be to create a machine learning model that learns from the historical publicly available data that contains simulated coordinate data and the true coordinate data and predicts the value which has less error as compared to SGP4-simulator. We will be using gradient boosting in this project. The machine learning model will lie somewhere in between the simulated value and the true value and thus will be suited well enough to improve the existing model. The accuracy of the existing model will be increased.
Space-Debris-Tracking
The full project for Nasa Space Apps Cairo
SpaceDebrisTracker
NASA Spaceapps Hackathon
debris-sequencer
Repository for Team Mün's solution for the 2021 NASA Space Apps - Space Debris Visualization Challenge
trashgazing
🌌 🚀 ☄ 🛰 A tool that visualizes space debris positions from your current location, for NASA Space Apps Hackathon 2018.
NASA-Project-Plastic-Marine-Debris-Classification-Machine-Learning-Software
NASA Project; Plastic Marine Debris Classification-Machine Learning Software
NASA-3D-Resources
Here you'll find a growing collection of 3D models, textures, and images from inside NASA.
MarshMorpho2D
2D long-term marsh evolution model based on tidal dispersion. See also: https://csdms.colorado.edu/wiki/Model:MarshMorpho2D
Mathematical-Modeling
数学建模常见模型及Python实现
Mathematical-modeling-algorithm-and-Application
数学建模算法与应用（司守奎，国防工业出版社）案例代码python实现
WiFi.Locate
Precision Positioning System using WiFi mathematically modeled using Machine Learning
Mathematical-Modeling
A sharing of the learning process of mathematical modeling 数学建模常用工具模型算法分享：数学建模竞赛优秀论文，数学建模常用算法模型，LaTeX论文模板，SPSS工具分享。