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这是物理学公式拟合工具PhySo(Φ-SO)的demo的中文注释项目,帮助需要快速入门此工具的**科研人员初步熟悉该工具的使用
California Institute of Technology provides ACN-DATA to help researchers access real data around electric vehicle charging. Here I have analysed the data and verified some of the user behaviour mentioned in "ACN-Data : Analysis and Applications of an Open EV Charging Dataset" paper. The link of the paper is : https://ev.caltech.edu/assets/pub/ACN_Data_Analysis_and_Applications.pdf
Research tools for the Adaptive Charging Network
Simple python example on how to use ARIMA models to analyze and predict time series.
🏆 A weekly updated ranked list of popular open-source libraries and tools for Power System Analysis.
Electromagnetic Transients Program (EMTP) of Bonneville Power Administration (BPA)
Buildings-to-Grid Integration Framework: Codes and Data
Data Analysis of EV charging Dataset by Elaad NL
Electric Vehicle Charging Infrastructure Simulator (ELVIS)
C++ translation from EMTA-BPA Fortran using fable
GNNs and Benchmarks for Node-level Load Forecasting
FB-interpreter is logic-arithmetic interpreter with variable and string support, build with Flex and Bison.
Simulate Functional Mockup Units (FMUs) in Python
Forecasting: Principles and Practice (2nd ed)
An Intuitive Tutorial to Gaussian Processes Regression
BPA ATP-EMTP translated into fortran 90.
Implementation of generative models to compute scenario of renewable generation and consumption.
Gaussian Mixture Models in Python
Code for predicting user behavior in this paper: https://ev.caltech.edu/assets/pub/ACN_Data_Analysis_and_Applications.pdf
Gaussian processes framework in python
Source Code for GridLAB-D
Source Code to go along with my video on how to program a gui in python using Tkinter
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
Introduction to time series preprocessing and forecasting in Python using AR, MA, ARMA, ARIMA, SARIMA and Prophet model with forecast evaluation.
Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models
周志华《机器学习》又称西瓜书是一本较为全面的书籍,书中详细介绍了机器学习领域不同类型的算法(例如:监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等),记录了本人在学习过程中的理解思路与扩展知识点,希望对新人阅读西瓜书有所帮助!
Get started with Machine Learning with Python - An introduction with Python programming examples
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.