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Category:All HeadlinesWorld & GeopoliticsMarkets & EconomyTech & AIPoliticsSearch results for: "Few-shot RUL prediction f" (7 stories)

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A degradation index model for maintenance prediction run-to-failure in production systems
Lead StoryNaturetech
Aug 6

A degradation index model for maintenance prediction run-to-failure in production systems

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFBxbmowX0NNOGIxX0tiZG40bmRBczNpU3VQaGE2ZWVnWVgteHduRE5UYTI3Z3dpbkpBSW1SeUUwSXAzLUxyVXpwVXZXZTFfa21aLVY5dXF4QUZVT1U4MjJv?oc=5" target="_blank">A degradation index model for maintenance prediction run-to-failure in production systems</a>  <font color="#6f6f6f">Nature</font>

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Search Results for "Few-shot RUL prediction f"

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6 stories displayed
A novel dual-dimensional contrastive self-supervised learning-based framework for rolling bearing remaining useful life prediction
Naturetech

A novel dual-dimensional contrastive self-supervised learning-based framework for rolling bearing remaining useful life prediction

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE1HT3FjSnhaMzVnZ2JESEJhWXR3eldZVGt3NGNXekV5dk5wbGNuSGs5OFFfOXQxdVZ1QjhJVERUaVVTR3dHRGZEOTFyN2dvWXdORTQtVXhLV01EeWRaWVUw?oc=5" target="_blank">A novel dual-dimensional contrastive self-supervised learning-based framework for rolling bearing remaining useful life prediction</a>  <font color="#6f6f6f">Nature</font>

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Few-shot RUL prediction for engines based on CNN-GRU model
Naturegeneral

Few-shot RUL prediction for engines based on CNN-GRU model

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE8yVDVYUmNLOUhBLXFxS1IwdVRDRzZyZE12czVLaVVxY1VOWGppdF9aRi1vNE5TWmg5UlVmZnVZVEhqU3lwQlVzR0owMUMyUjNiV3FFdGxPeWl2aDZNNzh3?oc=5" target="_blank">Few-shot RUL prediction for engines based on CNN-GRU model</a>  <font color="#6f6f6f">Nature</font>

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Remaining useful life prediction of lithium battery based on deep reinforcement learning fusion network
ScienceDirect.comtech

Remaining useful life prediction of lithium battery based on deep reinforcement learning fusion network

<a href="https://news.google.com/rss/articles/CBMie0FVX3lxTE5iVVdnS3pCQWJ2ZW1kWnlYamV0M0FpalBQT2ZwZXA3MXpEX0M5Y0lDaEtIMDEySzUteGhqLU1vR3BqMld1VlZBa0h5SVBoeWhTZTQwZGtOanhzczIyMlVLY1VDXzlzUTBVTjI4dFVoMjVXSE9Ya1d6R3VySQ?oc=5" target="_blank">Remaining useful life prediction of lithium battery based on deep reinforcement learning fusion network</a>  <font color="#6f6f6f">ScienceDirect.com</font>

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A TCN-Attention fusion model for fault prediction and remaining useful life estimation of large-scale mining equipment
Naturetech

A TCN-Attention fusion model for fault prediction and remaining useful life estimation of large-scale mining equipment

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE03LWl5Nm5oWGhYelBVYjNNSEZpUU9wTi0xRnY4UFVwVExMQi14ekZ1QkZnTFVHWmZLd0h4ci1KUUdHTVEtXzlfWkFrNGI0M0RNOUZYbnRMYmp0eDM3RjFr?oc=5" target="_blank">A TCN-Attention fusion model for fault prediction and remaining useful life estimation of large-scale mining equipment</a>  <font color="#6f6f6f">Nature</font>

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Few-shot cross-domain fault diagnosis via adversarial meta-learning
Naturetech

Few-shot cross-domain fault diagnosis via adversarial meta-learning

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTFBHYzQ3WHRIb1pGUkNJeFpMWlFSd0E4MG5fWENYT3MwWHJ4SmNvMkJLUGFjeW5iU0F0S2NvYkpXSE16dlFpYWZUVzNlR1FSMnZ1djh4blg1cHI4MmNOUjdj?oc=5" target="_blank">Few-shot cross-domain fault diagnosis via adversarial meta-learning</a>  <font color="#6f6f6f">Nature</font>

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Hybrid Gaussian process regression with temporal feature extraction for partially interpretable remaining useful life interval prediction in Aeroengine prognostics
Naturetech

Hybrid Gaussian process regression with temporal feature extraction for partially interpretable remaining useful life interval prediction in Aeroengine prognostics

<a href="https://news.google.com/rss/articles/CBMiX0FVX3lxTE5tYkJHUEdzRmNWajU3b2xQWE1aRmFPX3Fzcl84T3plQ1RsTkE5azB1UXoxSUJUMHNvR1BnTTFHWlVjYkJJV3RrakctcW9ueDFOLVhacHE2MHVjWUF4M0hJ?oc=5" target="_blank">Hybrid Gaussian process regression with temporal feature extraction for partially interpretable remaining useful life interval prediction in Aeroengine prognostics</a>  <font color="#6f6f6f">Nature</font>

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