Topic: prognostics Goto Github
Some thing interesting about prognostics
Some thing interesting about prognostics
prognostics,Statistical data analysis of the myocardial infarction for life or death prognosis using PCA method
User: anasoubaha
prognostics,Remaining Useful Life (RUL) prediction for Turbofan Engines
User: delta1epsilon
prognostics,remaining useful life, residual useful life, remaining life estimation, survival analysis, degradation models, run-to-failure models, condition-based maintenance, CBM, predictive maintenance, PdM, prognostics health management, PHM
User: ericlrf
prognostics,Open rotating mechanical fault datasets (开源旋转机械故障数据集整理)
User: hustcxl
prognostics,
User: john-zf
prognostics,Tidy multi-material machine tool wear dataset for prognostics and health monitoring.
Organization: katulu-io
prognostics,Wesendrup, Kevin; Hellingrath, Bernd (2023): ML2-enabled Condition-based Demand, Production, Inventory, and Maintenance Planning. In : IFAC World Congress 2023. IFAC World Congress 2023, pp. 7182–7187.
User: kev-wes
prognostics,NASA Livingstone-2 Oliver and L2 engine in Java and C++
User: masterskepticista
prognostics,Multi-Objective Optimization of ELM for RUL Prediction
User: mohyunho
prognostics,N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)
User: mohyunho
prognostics,Evolutionary Neural Architecture Search on Transformers for RUL Prediction
User: mohyunho
prognostics,The Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems, and provides a set of algorithms for state estimation and prediction, including uncertainty propagation. The algorithms take as inputs prognostic models (from NASA's Prognostics Model Package), and perform estimation and prediction functions. The library allows the rapid development of prognostics solutions for given models of components and systems. Different algorithms can be easily swapped to do comparative studies and evaluations of different algorithms to select the best for the application at hand.
Organization: nasa
prognostics,The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.
Organization: nasa
prognostics,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 one or more users to access the features of these packages through a REST API. The package is intended to be used as a research tool to prototype and benchmark Prognostics As-A-Service (PaaS) architectures and work on the challenges facing such architectures, including Generality, Communication, Security, Environmental Complexity, Utility, and Trust.
Organization: nasa
prognostics,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.
Organization: nasa
Home Page: https://nasa.github.io/progpy/
prognostics,A Prognosis Webpage that leverages the power of Chat-gpt 3.5.
User: ppraval
prognostics,A repository containing all data and project files pertaining to my Thesis.
User: y4shb
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