Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
-
Updated
Mar 17, 2023 - Python
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
Evolutionary Neural Architecture Search on Transformers for RUL Prediction
The NASA Prognostics As-A-Service (PaaS) Sandbox is a simplified implementation of a Software Oriented Architecture (SOA) for performing prognostics (estimation of time until events and future system states) of engineering systems. The PaaS Sandbox is a wrapper around the Prognostics Algorithms Package and Prognostics Models Package, allowing on…
The NASA Prognostic Python Packages is a Python framework focused on defining and building models and algorit for prognostics (computation of remaining useful life) of engineering systems, and provides a set of models and algorithms for select components developed within this framework, suitable for use in prognostic applications.
Machine learning algorithm to predict the long-term adverse cardiovascular events following coronary artery bypass surgery (CABG)
Add a description, image, and links to the prognostics-health-management topic page so that developers can more easily learn about it.
To associate your repository with the prognostics-health-management topic, visit your repo's landing page and select "manage topics."