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attention-based-cnn-bilstm-battery-soh-prediction

Attention-based CNN-BiLSTM for SOH prediction of lithium-ion batteries

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

bms-autoanalysis

books-free-books

免费书籍汇总。　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　 　 　 　 　 　 　 　

capstoneproject

Predicting the RUL of batteries using LSTM.

chatgpt_academic

科研工作专用ChatGPT拓展，特别优化学术Paper润色体验，支持自定义快捷按钮，支持自定义函数插件，支持markdown表格显示，Tex公式双显示，代码显示功能完善，新增本地Python/C++/Go项目树剖析功能/项目源代码自译解能力，新增PDF和Word文献批量总结功能

cnn-astlstm

Code for paper "An end-to-end neural network framework for SOH estimation and RUL prediction of lithium battery"

data-driven-prediction-of-battery-cycle-life-before-capacity-degradation

Code for Nature energy manuscript

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

deep-time-series

Deep learning PyTorch library for time series forecasting

ee7566-electrical-drives

METU EE75566 Electric Drives in Electric and Hybrid Electric Vehicles by Emine Bostancı

electrical-vehicle-v2g

electrical vehicle

keras-lithium-ion-battery-state-of-health-estimation-based-on-battery-temperature

To estimate the battery SoH from the differences in temperature, LSTM Network is utilized to estimate the remaining SoH based on the battery state of temperature.

matlab-microgrid-components

A simulation to find the optimized sizes of microgrid components (PV and battery) constrained by a certain acceptable loss of load percentage and by budget. This simulation is written by Stefano Mandelli and expanded by Håkon Duus.

nasa_li-ion_battery_soh_prediction_with_mvip-trans

This research provides a prognostic framework for off-line SOH estimation of Li-ion battery. With a CNN-Transformer architecture, this program is capable of modeling the temporal correlations of battery signals from both local and global views. In this way, the learning ability of both local features and long period contexts will be enhanced.

phm_wechat_app

基于工业phm领域的轴承故障预测前端微信小程序

pinn-battery-prognostics

State of Health (SoH) and Remaining Useful Life (RUL) prediction for Li-ion batteries based on Physics-Informed Neural Networks (PINN).

plms-in-practical-kbqa

The code of An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering

pythonteaching

Courses for College Students

seaborn

Statistical data visualization in Python

soh-estimation

Lithium ion battery state of health estimation and remaining useful life prediction using ELM

soh_estimation_of_lithium-ion_battery

State of health (SOH) prediction for Lithium-ion batteries using regression and LSTM

timeseries

Timeseries for everyone