andresrodriguez55/wind-turbines-edge-ai
BACHELOR THESIS. Detect wind turbine errors using a hybrid model. Utilize ML, DL, edge computing. Dataset, neural network optimized with genetic algorithms. Low computational power ML models. Data is stored in the cloud. Turbine status via secure APIs. Password encryption. GRASP, SOLID
No commits in the last 6 months.
Stars
14
Forks
1
Language
Java
License
—
Category
Last pushed
Jun 02, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/andresrodriguez55/wind-turbines-edge-ai"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
petrobras/BibMon
Python package that provides predictive models for fault detection, soft sensing, and process...
hustcxl/Deep-learning-in-PHM
Deep learning in PHM，Deep learning in fault diagnosis，Deep learning in remaining useful life prediction
kokikwbt/predictive-maintenance
Datasets for Predictive Maintenance
biswajitsahoo1111/rul_codes_open
This repository contains code that implement common machine learning algorithms for remaining...
tvhahn/weibull-knowledge-informed-ml
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets....