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Risk-based renewal planning for asset management of water distribution systems
An Empirical Study on ML Asset Management
this repo use to simulate Joint optimization decision of condition-based maintenance and spare parts inventory
Grid2Op a testbed platform to model sequential decision making in power systems.
Additional material for "Graph Signal Processing on Complex Networks for Structural Health Monitoring"
LSTMS for Predictive Maintenance
Maintenance Optimization Problem. A mixed integer optimization model for maintenance operations to minimize the Total Cost and obtain the optimal value of decision variables.
maintenance-replacement optimization problem, where the goal is to optimize the decision of when to replace a machine based on its age and associated costs. This problem is relevant in many industries, where machines are critical for production and the decision of when to replace them can have a significant impact on costs and performance.
Evolutionary multi-objective optimization platform
Optimize maintenance schedule for gas turbine
Predicting the Remaining Useful Life (RUL) of simulated turbofan data using Keras and LSTM.
In this project I aim to apply Various Predictive Maintenance Techniques to accurately predict the impending failure of an aircraft turbofan engine.
Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.
A notebook tutorial series for performing predictive maintenance using machine learning
Predictive maintenance solution. 1D CNN model in TensorFlow 2.0 with Azure Machine Learning. Tf-Lite Model Optimization
Papers and datasets for Vibration Analysis
Data for our paper "Scientometric Review of Artificial Intelligence for Operations & Maintenance of Wind Turbines: The Past, Present and Future".
Tensorforce: a TensorFlow library for applied reinforcement learning
The Water Pump Maintenance Break Prediction project uses machine learning and sensor data to predict maintenance needs, improving pump efficiency and reducing downtime. It highlights the importance of predictive maintenance and data-driven decision-making in optimizing industrial operations and ensuring water supply management.
The wind turbine failure dataset (SCADA – Supervisory Control and Data Acquisition) has measurements recorded every 10 seconds, from wind turbine sensors. The variable names are unknown, but they represent sensor measurements that correspond to various physical process properties.
Wind Turbine Fault Detection. Newer version @ https://github.com/lkev/wtphm
Wind Turbine Fault Identification using Machine Learning Techniques applied to SCADA data
SCADA data pre-processing library for prognostics, health management and fault detection of wind turbines. Successor to https://github.com/lkev/wt-fdd
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.