Imagen de Portada

AI-driven Transformer Model for Fault Prediction in Non-Linear Dynamic Automotive System

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Kumar, Priyanka
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Evaluation of Artificial Intelligence Methods for Lead Time Prediction in Non-Cycled Areas of Automotive Production
por: Hake, Cornelius, et al.
Publicado: (2025)

Power Transformer Fault Prediction Based on Knowledge Graphs
por: Wang, Chao, et al.
Publicado: (2024)

Data-driven Machinery Fault Diagnosis: A Comprehensive Review
por: Neupane, Dhiraj, et al.
Publicado: (2024)

UrbanAI 2025 Challenge: Linear vs Transformer Models for Long-Horizon Exogenous Temperature Forecasting
por: Gokhman, Ruslan
Publicado: (2025)

SETA: Statistical Fault Attribution for Compound AI Systems
por: Chowdhury, Sayak, et al.
Publicado: (2026)

GoldenTransformer: A Modular Fault Injection Framework for Transformer Robustness Research
por: Howard, Luke
Publicado: (2025)

Twin Transformer using Gated Dynamic Learnable Attention mechanism for Fault Detection and Diagnosis in the Tennessee Eastman Process
por: Labbaf-Khaniki, Mohammad Ali, et al.
Publicado: (2024)

AB-UPT for Automotive and Aerospace Applications
por: Alkin, Benedikt, et al.
Publicado: (2025)

Transformers Linearly Represent Highly Structured World Models
por: Kniazev, Roman, et al.
Publicado: (2026)

Coarsening Linear Non-Gaussian Causal Models with Cycles
por: Madaleno, Francisco, et al.
Publicado: (2026)

TRISKELION-1: Unified Descriptive-Predictive-Generative AI
por: Kumar, Nardeep, et al.
Publicado: (2025)

DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT Systems
por: Zhao, Mengjie, et al.
Publicado: (2023)

Large-Step Training Dynamics of a Two-Factor Linear Transformer Model
por: Balasubramanian, Krishnakumar
Publicado: (2026)

STLGT: A Scalable Trace-Based Linear Graph Transformer for Tail Latency Prediction in Microservices
por: Ding, Yongliang, et al.
Publicado: (2026)

Univariate Skeleton Prediction in Multivariate Systems Using Transformers
por: Morales, Giorgio, et al.
Publicado: (2024)

FaultDiffusion: Few-Shot Fault Time Series Generation with Diffusion Model
por: Xu, Yi, et al.
Publicado: (2025)

Application of Reduced-Order Models for Temporal Multiscale Representations in the Prediction of Dynamical Systems
por: Ghazal, Elias Al, et al.
Publicado: (2025)

One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning
por: He, Bowen, et al.
Publicado: (2026)

Conformal Prediction on Quantifying Uncertainty of Dynamic Systems
por: Liang, Aoming, et al.
Publicado: (2024)

Global-Lens Transformers: Adaptive Token Mixing for Dynamic Link Prediction
por: Zou, Tao, et al.
Publicado: (2025)

Physics-Guided Tiny-Mamba Transformer for Reliability-Aware Early Fault Warning
por: Li, Changyu, et al.
Publicado: (2026)

Linear Chain Transformation: Expanding Optimization Dynamics for Fine-Tuning Large Language Models
por: Wang, Yulong, et al.
Publicado: (2024)

AB-UPT: Scaling Neural CFD Surrogates for High-Fidelity Automotive Aerodynamics Simulations via Anchored-Branched Universal Physics Transformers
por: Alkin, Benedikt, et al.
Publicado: (2025)

FaultXformer: A Transformer-Encoder Based Fault Classification and Location Identification model in PMU-Integrated Active Electrical Distribution System
por: Thakur, Kriti, et al.
Publicado: (2026)

Fault Analysis And Predictive Maintenance Of Induction Motor Using Machine Learning
por: Venkatesh, Kavana, et al.
Publicado: (2024)

Reviewing AI's Role in Non-Muscle-Invasive Bladder Cancer Recurrence Prediction
por: Abbas, Saram, et al.
Publicado: (2024)

AI-Driven Intrusion Detection Systems (IDS) on the ROAD Dataset: A Comparative Analysis for Automotive Controller Area Network (CAN)
por: Guerra, Lorenzo, et al.
Publicado: (2024)

Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecasting
por: Lu, Jiecheng, et al.
Publicado: (2025)

Generalizing Orthogonalization for Models with Non-Linearities
por: Rügamer, David, et al.
Publicado: (2024)

Global Attention with Linear Complexity for Exascale Generative Data Assimilation in Earth System Prediction
por: Wang, Xiao, et al.
Publicado: (2026)

Automotive Crash Dynamics Modeling Accelerated with Machine Learning
por: Nabian, Mohammad Amin, et al.
Publicado: (2025)

Dynamic QoS Prediction via a Non-Negative Tensor Snowflake Factorization
por: Xia, YongHui, et al.
Publicado: (2025)

Distilling Linearized Behavior into Non-Linear Fine-Tuning for Effective Task Arithmetic
por: Sommariva, Thomas, et al.
Publicado: (2026)

Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids
por: Ardito, Carmelo, et al.
Publicado: (2023)

On the (Non) Injectivity of Piecewise Linear Janossy Pooling
por: Reshef, Ilai, et al.
Publicado: (2025)

Transolver is a Linear Transformer: Revisiting Physics-Attention through the Lens of Linear Attention
por: Hu, Wenjie, et al.
Publicado: (2025)

Performance Insights-based AI-driven Football Transfer Fee Prediction
por: Sulimov, Daniil
Publicado: (2024)

An Innovative Next Activity Prediction Using Process Entropy and Dynamic Attribute-Wise-Transformer in Predictive Business Process Monitoring
por: Zare, Hadi, et al.
Publicado: (2025)

ProDER: A Continual Learning Approach for Fault Prediction in Evolving Smart Grids
por: Efatinasab, Emad, et al.
Publicado: (2025)

IRNN: Innovation-driven Recurrent Neural Network for Time-Series Data Modeling and Prediction
por: Zhou, Yifan, et al.
Publicado: (2025)