yx577 Goto Github PK
Type: User
Company: Sun Yat-sen University
Location: Guangzhou
Type: User
Company: Sun Yat-sen University
Location: Guangzhou
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My 2-day short course on spatial data analytics and geostatistics. I hope these resources are helpful, Prof. Michael Pyrcz
A beginner's guide to carry out extreme value analysis, which consists of basic steps, multiple distribution fitting, confidential intervals, IDF/DDF, and a simple application of IDF information for roof drainage design. The guide mainly focuses on extreme rainfall analysis. However, the basic steps are also suitable for other climatic or hydrologic variables such as temperature, wind speed or runoff.
Air quality - machine learning classification
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
Created to automate the climatological analysis workflows USACE Regulatory Project Managers are required to perform to comply with long-standing agency guidance as well as the new Navigable Waters Protection Rule, effective June 22, 2020..
Materials for reproducing figures from Applegate et al. (2015, Climate Dynamics)
Data for Water Resource Management
This is a multi-objective optimization with constriant NSGA-2
A machine-learning application for short term day trading with prediction governed by linear Support Vector Machine (SVM) in python using scikit learn
Probabilistic Flood Risk Analysis to Support Risk Informed Decision-Making: Examples and Materials
Datasets, code and virtual workspace for the Climate Change ATLAS
This repository is under construction. It will be used to store all necessary function for the downscaling of atmspheric forcing variables.
A statistical downscaling approach using ConvLSTMs.
A curated list of awesome Python libraries, software and resources in Atmosphere, Environment and Machine Learning
R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''
Dissertation for my MSc in Smart Cities and Urban Analytics (UCL CASA)
R package to conduct univariate and bivariate wavelet analyses
Time series regression models using ARIMA, SARIMAX, and Recursive Neural Network to predict day-ahead and hour-ahead California wholesale electricity prices. Features include demand forecasts, NOAA weather station data, and CA Dept. of Water Resources reservoir water level hourly observation.
Precipitation-based indices are generally considered as the simplest indices because they are calculated solely based on long-term rainfall records that are often available. The mostly used precipitation-based indices consist of Decile Index (DI) Hutchinson Drought Severity Index (HDSI) Percen of Normal Index (PNI) Z-Score Index (ZSI) China-Z Index (CZI) Modified China-Z Index (MCZI) Rainfall Anomaly Index (RAI) Effective Drought Index (EDI) Standardized Precipitation Index (SPI).
👣 Calculate your carbon footprint easily using a command line interface (.PDF report).
The Climate Data Toolbox for MATLAB
for de-noising
Chaotic Statistical Downscaling
Tools and scripts for Water Resources Research (2017) paper
Code used for the analysis and visualisation of climate data during my PhD
Climate Statistics with Python.
An R Framework for Climate Data Access and Post-processing
Climate indices for drought monitoring, community reference implementations in Python
Collection of tools for CMIP5/6 files processing
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.