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A curated list of resources for genetic programming.
Perform data driven modelling of Li-ion batteries using convex optimization for parametrization of RC link models from open source testing datasets.
Developed a data-driven prognostic model using the Long short-term memory (LSTM) algorithm to predict the state of charge (SoC) and state of health (SoH) of the lithium-ion battery where the dataset was taken from the NASA Repository. The proposed LSTM algorithm was compared against other deep learning algorithms based on RMSE value.
Deep learning and LSTM approaches for human activity recognition
python-wrapped version of ellen, a linear genetic programming system for symbolic regression and classification.
GP-based classifiers benchmark
The available capacity of a battery, called the state of charge, is a fundamental characteristic for energy storage applications or electric vehicles. In order to model the state of charge of a lithium-ion battery using data-driven techniques, complex algorithms should be used so the dynamic behaviours of the battery are captured. An ensemble decis
Machine-learning approach In this work, author has developed data-driven models that accurately predict the cycle life of commercial lithium iron phosphate (LFP)/ graphite cells using early-cycle data, with no prior knowledge of degradation mechanisms. To build an early-prediction model, a feature-based approach is used. Features, such as initial
Multidimensional genetic programming for multiclass classification
Contains data preprocessing and visualization methods for ADL datasets.
An easy-to-use scikit-learn inspired implementation of the Standard Genetic Programming (StdGP) algorithm.
This repository illustrates how to model based on ECM and Data Driven techniques LiFePo types of battery packs used for E-mobility and Robotics applications. The main goal is to simulate the behavior of the battery during charge and discharge cycles while feeding a BLDC motor in order to study and map the SoC of the battery
Repository where the content of the SDHAR-HOME database is hosted, as well as the Python code to use it. Pending to be published.
SmartHomeHARLib is a small library to implement, test, and evaluate Smart Home Human Activity Recognition algorithms. Many algorithms and datasets exist in the litterature. This library try to contain most as possible datasets and algorithms for research in the Human Activity Recognition (HAR) for Smart Home field.
A living benchmark framework for symbolic regression
Helps you select the optimal cell to electrify a long-haul truck from a database containing 160 cells.
Battery design method for battery-electric long-haul trucks
Data and code for the paper "Ultra-early prediction of lithium-ion battery performance using mechanism and data-driven fusion model"
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.