Copertina

Reinforced Symbolic Learning with Logical Constraints for Predicting Turbine Blade Fatigue Life

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Li, Pei, Choi, Joo-Ho, Zhang, Dingyang, Zhang, Shuyou, Zhang, Yiming
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence Computational Engineering, Finance, and Science
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

FLOATBench: A Dataset and Benchmark for Floating Offshore Wind Turbine Tower Fatigue
di: Ribeiro, João Alves, et al.
Pubblicazione: (2026)

Fine-Tuning Pre-trained Large Time Series Models for Prediction of Wind Turbine SCADA Data
di: Fan, Yuwei, et al.
Pubblicazione: (2024)

Integrating Physics and Data-Driven Approaches: An Explainable and Uncertainty-Aware Hybrid Model for Wind Turbine Power Prediction
di: Gijón, Alfonso, et al.
Pubblicazione: (2025)

Avocado Price Prediction Using a Hybrid Deep Learning Model: TCN-MLP-Attention Architecture
di: Zhang, Linwei, et al.
Pubblicazione: (2025)

End-to-End Probabilistic Framework for Learning with Hard Constraints
di: Utkarsh, Utkarsh, et al.
Pubblicazione: (2025)

Flexible Parallel Neural Network Architecture Model for Early Prediction of Lithium Battery Life
di: Jiang, Lidang, et al.
Pubblicazione: (2024)

ARTEMIS: A Neuro Symbolic Framework for Economically Constrained Market Dynamics
di: Ray, Rahul D
Pubblicazione: (2026)

Unveiling Discrete Clues: Superior Healthcare Predictions for Rare Diseases
di: Zhao, Chuang, et al.
Pubblicazione: (2025)

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems
di: Zhang, Pei, et al.
Pubblicazione: (2024)

MTPNet: Multi-Grained Target Perception for Unified Activity Cliff Prediction
di: Shu, Zishan, et al.
Pubblicazione: (2025)

Bitcoin Price Prediction using Machine Learning and Combinatorial Fusion Analysis
di: Wu, Yuanhong, et al.
Pubblicazione: (2026)

Reinforcement Learning with LLM-Guided Action Spaces for Synthesizable Lead Optimization
di: Li, Tao, et al.
Pubblicazione: (2026)

Optimize Flip Angle Schedules In MR Fingerprinting Using Reinforcement Learning
di: Zhong, Shenjun, et al.
Pubblicazione: (2025)

Ensemble Methodology:Innovations in Credit Default Prediction Using LightGBM, XGBoost, and LocalEnsemble
di: Zhu, Mengran, et al.
Pubblicazione: (2024)

Out-of-Distribution Generalized Dynamic Graph Neural Network for Human Albumin Prediction
di: Zhang, Zeyang, et al.
Pubblicazione: (2023)

RLDBF: Enhancing LLMs Via Reinforcement Learning With DataBase FeedBack
di: Dai, Weichen, et al.
Pubblicazione: (2025)

Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning
di: Jimenez-Roa, Lisandro A., et al.
Pubblicazione: (2024)

Neuro-Symbolic Financial Reasoning via Deterministic Fact Ledgers and Adversarial Low-Latency Hallucination Detector
di: Agand, Pedram
Pubblicazione: (2026)

Instructor-inspired Machine Learning for Robust Molecular Property Prediction
di: Wu, Fang, et al.
Pubblicazione: (2023)

DeepFEA: Deep Learning for Prediction of Transient Finite Element Analysis Solutions
di: Triantafyllou, Georgios, et al.
Pubblicazione: (2024)

FutureX-Pro: Extending Future Prediction to High-Value Vertical Domains
di: Liu, Jiashuo, et al.
Pubblicazione: (2026)

BikeBench: A Bicycle Design Benchmark for Generative Models with Objectives and Constraints
di: Regenwetter, Lyle, et al.
Pubblicazione: (2025)

Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools
di: Zhang, Wentao, et al.
Pubblicazione: (2023)

Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
di: Li, Ruikun, et al.
Pubblicazione: (2025)

Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns
di: Zhu, Haoren, et al.
Pubblicazione: (2024)

Beyond the Norm: A Survey of Synthetic Data Generation for Rare Events
di: Gu, Jingyi, et al.
Pubblicazione: (2025)

AIGB: Generative Auto-bidding via Conditional Diffusion Modeling
di: Guo, Jiayan, et al.
Pubblicazione: (2024)

FinRule-Bench: A Benchmark for Joint Reasoning over Financial Tables and Principles
di: Malarkkan, Arun Vignesh, et al.
Pubblicazione: (2026)

Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling
di: Zeng, Liang, et al.
Pubblicazione: (2021)

TFG-Flow: Training-free Guidance in Multimodal Generative Flow
di: Lin, Haowei, et al.
Pubblicazione: (2025)

Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer
di: Yu, Youn-Yeol, et al.
Pubblicazione: (2023)

MANA-Net: Mitigating Aggregated Sentiment Homogenization with News Weighting for Enhanced Market Prediction
di: Wang, Mengyu, et al.
Pubblicazione: (2024)

Precise Antigen-Antibody Structure Predictions Enhance Antibody Development with HelixFold-Multimer
di: Gao, Jie, et al.
Pubblicazione: (2024)

Predicting Stock Movement with BERTweet and Transformers
di: Albada, Michael Charles, et al.
Pubblicazione: (2025)

Off-the-Shelf Neural Network Architectures for Forex Time Series Prediction come at a Cost
di: Zafeiriou, Theodoros, et al.
Pubblicazione: (2024)

StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
di: Wang, Shengkun, et al.
Pubblicazione: (2024)

The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering
di: Li, Hao, et al.
Pubblicazione: (2025)

Topic Modeling and Link-Prediction for Material Property Discovery
di: Barron, Ryan C., et al.
Pubblicazione: (2025)

Benchmarking Machine Learning Uncertainty Quantification Methodologies for Predicting Turbine Gas Temperature Degradation
di: Barry-Straume, Jostein, et al.
Pubblicazione: (2026)

Foam-Agent 2.0: An End-to-End Composable Multi-Agent Framework for Automating CFD Simulation in OpenFOAM
di: Yue, Ling, et al.
Pubblicazione: (2025)