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[Project Addition] : Condition monitoring using DL #698
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Our team will soon review your PR. Thanks @jeet-Abhi123 :) |
abhisheks008
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Approved @jeet-Abhi123
abhisheks008
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Status: Approved
Approved PR by the PA.
level 2
Level 2 for GSSOC
gssoc
Girlscript Summer of Code 2024
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Jun 2, 2024
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Girlscript Summer of Code 2024
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Status: Approved
Approved PR by the PA.
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Pull Request for DL-Simplified 💡
#680 : Condition monitoring using DL
Closes: #680
Describe the add-ons or changes you've made 📃
The GRU model outperformed the LSTM and CNN models in terms of test loss, making it the most effective model for predicting the Remaining Useful Life (RUL) of airplane turbofan engines in this project. However, each model brings unique strengths, and further optimization and ensemble methods could potentially improve overall performance.
By leveraging these advanced neural network models, the project aims to provide accurate RUL predictions, contributing to proactive maintenance scheduling and enhanced operational efficiency in aviation.
How Has This Been Tested? ⚙️
Describe how it has been tested
I have tested the implementation using a separate test dataset and verified the classification accuracy of each model. Additionally, I have compared the results with the expected outcomes to ensure accuracy.
Checklist: ☑️