Rex Deng's repositories
Air-Quality-Prediction-
Generally, Air pollution refers to the release of pollutants into the air that are detrimental to human health and the planet as a whole. It can be described as one of the most dangerous threats that the humanity ever faced. It causes damage to animals, crops, forests etc. To prevent this problem in transport sectors have to predict air quality from pollutants using machine learning techniques. Hence, air quality evaluation and prediction has become an important research area. The aim is to investigate machine learning based techniques for air quality forecasting by prediction results in best accuracy. The analysis of dataset by supervised machine learning technique(SMLT) to capture several information’s like, variable identification, uni-variate analysis, bi-variate and multi-variate analysis, missing value treatments and analyse the data validation, data cleaning/preparing and data visualization will be done on the entire given dataset. Our analysis provides a comprehensive guide to sensitivity analysis of model parameters with regard to performance in prediction of air quality pollution by accuracy calculation. To propose a machine learning-based method to accurately predict the Air Quality Index value by prediction results in the form of best accuracy from comparing supervise classification machine learning algorithms. Additionally, to compare and discuss the performance of various machine learning algorithms from the given transport traffic department dataset with evaluation of GUI based user interface air quality prediction by attributes.
Air_pollution_clustering
Finding similarities, aka as clustering, in air polution of multiple areas of India. The dataset comprises three types of air pollutant in India for specific cities. Techniques used: K-means clustering, Hierarchical Clustering, Affinity Propagation, Agglomerative Clustering, BIRCH Clustering, DBSCAN and Gaussian Mixture Model.
Auto-Review-Generator
自动读取本地pdf文献并提取标题、作者、摘要和结论生成综述。Read and translate English literature to generate review automatically.
CFDofReactiveFlows
Collection of codes in Matlab(R) and C++ for solving basic problems presented and discussed in the "Computational Fluid Dynamics of Reactive Flows" course (Politecnico di Milano)
CFDPython
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
d2l-zh
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被60多个国家的400多所大学用于教学。
Exam-Portal
Online Examination system made using Django
GLM
Code for the General Lake Model
glmtools
Tools for interacting with the General Lake Model (GLM) in R
GreenFoot_Dev
Creation of an interactive map in R language using leaflet and shiny (web app). It displays some information about sport facilities in world.
h2o-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
lake-temperature-model-prep
Pipeline #1
LakeEnsemblR
An R package that facilitates multi-model ensembles for lake thermodynamics. Also includes tools for calibration, sensitivity analysis and data visualization.
LakeEnsemblR.WQ
R Package to facilitate running ensembles of water quality models
LakeTrophicModelling
ORD LakeTrophicModelling
LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
mda.lakes
Wisconsin Lake Modeling Aggregation
MTS-Mixers
MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing
multiple_velocity_fields_visualization
Files for the cross-validation of the SVM and GPR for flow approximation when clouds are flowing in one wind velocity field or two different wind velocity fields
PaddleTS
Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
PointPolygon
Repo for Simulating and Testing Point Polygon Strategies
pubtrends-nature-reviews
The source code for PubTrends topics optimization
pubtrends-review
Automatic generation of reviews of scientific papers
Python-Language-Programming
电子科技大学2020年《Python语言程序设计》的平时作业和期末课设。平时作业共4次，每次有25道编程题和100道单项选择题；课设题目是自动组卷评卷考试系统。
shiny-gallery
Code and other documentation for apps in the Shiny Gallery ✨
Simstrat
Simstrat - 1D lake model
tpot
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
transferlearning
Everything about Transfer Learning and Domain Adaptation--迁移学习
water-quality-analysis
R scripts to calculate water quality trends and the water quality index at selected ambient monitoring stations in B.C.
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow