Copertina

A temporal scale transformer framework for precise remaining useful life prediction in fuel cells

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Tang, Zezhi, Chen, Xiaoyu, Jin, Xin, Zhang, Benyuan, Liang, Wenyu
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Hierarchical Testing with Rabbit Optimization for Industrial Cyber-Physical Systems
di: Hu, Jinwei, et al.
Pubblicazione: (2025)

Hybrid quantum recurrent neural network for remaining useful life prediction
di: Tsurkan, Olga, et al.
Pubblicazione: (2025)

Temporal convolutional and fusional transformer model with Bi-LSTM encoder-decoder for multi-time-window remaining useful life prediction
di: Pour, Mohamadreza Akbari, et al.
Pubblicazione: (2025)

RULSurv: A probabilistic survival-based method for early censoring-aware prediction of remaining useful life in ball bearings
di: Lillelund, Christian Marius, et al.
Pubblicazione: (2024)

A federated learning framework with knowledge graph and temporal transformer for early sepsis prediction in multi-center ICUs
di: Chang, Yue, et al.
Pubblicazione: (2026)

Federated learning framework for collaborative remaining useful life prognostics: an aircraft engine case study
di: Landau, Diogo, et al.
Pubblicazione: (2025)

Easy attention: A simple attention mechanism for temporal predictions with transformers
di: Sanchis-Agudo, Marcial, et al.
Pubblicazione: (2023)

Remaining useful life prediction of Lithium-ion batteries using spatio-temporal multimodal attention networks
di: Suh, Sungho, et al.
Pubblicazione: (2023)

Static and multivariate-temporal attentive fusion transformer for readmission risk prediction
di: Sun, Zhe, et al.
Pubblicazione: (2024)

Pretrained battery transformer (PBT): A foundation model for universal battery life prediction
di: Tan, Ruifeng, et al.
Pubblicazione: (2025)

Decomposition-based multi-scale transformer framework for time series anomaly detection
di: Zhang, Wenxin, et al.
Pubblicazione: (2025)

Sparsity-Constraint Optimization via Splicing Iteration
di: Zhu, Jin, et al.
Pubblicazione: (2024)

Universal crystal material property prediction via multi-view geometric fusion in graph transformers
di: Zhang, Liang, et al.
Pubblicazione: (2025)

Lower bounds on transformers with infinite precision
di: Kozachinskiy, Alexander
Pubblicazione: (2024)

FWin transformer for dengue prediction under climate and ocean influence
di: Tran, Nhat Thanh, et al.
Pubblicazione: (2024)

GeOT: A spatially explicit framework for evaluating spatio-temporal predictions
di: Wiedemann, Nina, et al.
Pubblicazione: (2024)

Hybrid machine learning based scale bridging framework for permeability prediction of fibrous structures
di: Korolev, Denis, et al.
Pubblicazione: (2025)

Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics
di: Wang, Zijian, et al.
Pubblicazione: (2025)

Accurate ignition detection of solid fuel particles using machine learning
di: Li, Tao, et al.
Pubblicazione: (2023)

ADCNet: a unified framework for predicting the activity of antibody-drug conjugates
di: Chen, Liye, et al.
Pubblicazione: (2024)

A framework for probabilistic prediction of remaining useful life in structural materials
di: Maudonet, Victor, et al.
Pubblicazione: (2024)

PULSE: Generative Phase Evolution for Non-Stationary Time Series Forecasting
di: Liu, Yangyou, et al.
Pubblicazione: (2026)

skscope: Fast Sparsity-Constrained Optimization in Python
di: Wang, Zezhi, et al.
Pubblicazione: (2024)

Modeling Spatio-temporal Extremes via Conditional Variational Autoencoders
di: Ma, Xiaoyu, et al.
Pubblicazione: (2025)

Integrating attention into explanation frameworks for language and vision transformers
di: Eggen, Marte, et al.
Pubblicazione: (2025)

Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered care
di: Anuyah, Sydney, et al.
Pubblicazione: (2024)

Rethinking deep learning: linear regression remains a key benchmark in predicting terrestrial water storage
di: Nie, Wanshu, et al.
Pubblicazione: (2025)

Atlantes: A system of GPS transformers for global-scale real-time maritime intelligence
di: Herzog, Henry, et al.
Pubblicazione: (2025)

Neural Canonical Polyadic Factorization for Traffic Analysis
di: Luo, Wenyu, et al.
Pubblicazione: (2025)

The geomagnetic storm and Kp prediction using Wasserstein transformer
di: Li, Beibei
Pubblicazione: (2025)

Real-time object detection and robotic manipulation for agriculture using a YOLO-based learning approach
di: Zhao, Hongyu, et al.
Pubblicazione: (2024)

DURENDAL: Graph deep learning framework for temporal heterogeneous networks
di: Dileo, Manuel, et al.
Pubblicazione: (2023)

A predictive machine learning force field framework for liquid electrolyte development
di: Gong, Sheng, et al.
Pubblicazione: (2024)

Quantized Evolution Strategies: High-precision Fine-tuning of Quantized LLMs at Low-precision Cost
di: Xu, Yinggan, et al.
Pubblicazione: (2026)

Heterogeneous treatment effect estimation with subpopulation identification for personalized medicine in opioid use disorder
di: Lee, Seungyeon, et al.
Pubblicazione: (2024)

Finite State Automata Inside Transformers with Chain-of-Thought: A Mechanistic Study on State Tracking
di: Zhang, Yifan, et al.
Pubblicazione: (2025)

A deformation-based framework for learning solution mappings of PDEs defined on varying domains
di: Xiao, Shanshan, et al.
Pubblicazione: (2024)

ORIGAMI: A generative transformer architecture for predictions from semi-structured data
di: Rückstieß, Thomas, et al.
Pubblicazione: (2024)

A temporal deep learning framework for calibration of low-cost air quality sensors
di: Sengupta, Arindam, et al.
Pubblicazione: (2026)

Applications of temporal graph learning for predicting the dynamics of biological systems
di: Dileo, Manuel, et al.
Pubblicazione: (2026)