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1–50 von 520 Ergebnissen
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    Accelerating In-Vehicle Network Intrusion Detection System Using Binarized Neural Network

    Ma, Di / Zhang, Linxi / Yan, Xuke | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    A Combined Markov Chain and Reinforcement Learning Approach for Powertrain-Specific Driving Cycle Generation

    Dietrich, Maximilian / Sarkar, Mouktik / Chen, Xi | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    A Comparative Study of Longitudinal Vehicle Control Systems in Vehicle-to-Infrastructure Connected Corridor

    Fitzpatrick, Benjamin / King, Brian / Yoon, Hwan-Sik et al. | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    A Comparative Study of Recurrent Neural Network Architectures for Battery Voltage Prediction

    ZHU, DI / Cho, Gyouho / Campbell, Jeffrey | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Comparative Study with J48 and Random Tree Classifier for Predicting the State of Hydraulic Braking System through Vibration Signals

    Gopalan, Anitha / Arockia Dhanraj, Joshuva / Subramaniam, Mohankumar et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Comparison Study on Control Strategies for Optimization of an Anti-Lock Brake System Algorithm Based on Tire Force Measurement in Pure and Combined Slip Conditions of an Automobile

    Mehta, Harshal Piyush / Maurya, Mithilesh / Shaikh, Parvez Shagir et al. | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    A Comprehensive Analysis of Methods to Write Requirements for Machine Learning Components used in Autonomous Vehicles

    Gil Batres, Andrea / Avalos Gonzalez, Carlos / Krishnamoorthy, Jayalekshmi et al. | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    Acoustic Model Reduction for the Design of Acoustic Treatments

    Poulos, Athanasios / Jacqmot, Jonathan / Kayvantash, Kambiz et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Crack Detection Method for Self-Piercing Riveting Button Images through Machine Learning

    Freis, Amanda / Huff, Garret / Huang, Li et al. | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    Active-Learning Method: An Effective Way to Generate Ground Truth Data to Test & Validate ADAS Function Development

    Kumari, Anita / Katariya, Rashmi | SAE Technical Papers | 2024
    Schlagwörter: Machine learning

    A Decentralized Multi-agent Energy Management Strategy Based on a Look-Ahead Reinforcement Learning Approach

    Khalatbarisoltani, Arash / Boulon, Loic / Kandidayeni, Mohsen et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Decision-Making Method for Connected Autonomous Driving Based on Reinforcement Learning

    Zhang, Mingheng / Lv, Xinfei / Wan, Xing et al. | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    A Deep Ensemble Network Model for Refined Traffic Volume Prediction Considering Spatial-Temporal Features

    Tao, Lu / Zhou, Tian / Liu, Wan et al. | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    A Deep Learning-Based Strategy to Initiate Diesel Particle Filter Regeneration

    Roettger, Daniel / De Smet, Frederik / Fan, Ke et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Diagnostic Technology of Powertrain Parts that Cause Abnormal Noises Using Artificial Intelligence

    Lee, Dongchul / Yoo, Dongkyu / Jung, Insoo et al. | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    A Digital Forensic Method to Detect Object based Video Forgery Security Attacks on Surround View ADAS Camera System

    Karki, Maya / S M, Sarala | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Digital Twin Based Approach for Simulation and Emulation of an Automotive Paint Workshop

    Ruperez lng, Adrián / Martinez, Aitor / Lopez, Blanca et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    Adjoint-Based Model Tuning and Machine Learning Strategy for Turbulence Model Improvement

    Ren, Chao / Wu, Haibo / Zhou, Hua et al. | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    Advanced Modelling of Frequency Dependent Damper Using Machine Learning Approach for Accurate Prediction of Ride and Handling Performances

    Thanapati, Alok Ranjan / Anthonysamy, Baskar / Deshmukh, Chandrakant Ramrao et al. | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    Aeroengine Gas Path Parameter Trend Prediction Based on LSTM

    Zhou, Qifeng / Chen, Xiaonan / Qing, Xinlin et al. | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    A Forward Collision Warning System Using Deep Reinforcement Learning

    Dargahi, Javad / Zadeh, Mehrdad / Fekri, Pedram et al. | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    A Framework for Benchmarking Feedback-Based Dynamic Data Collection Methods in Connected Vehicle Networks

    Sahin, Alp / Zeng, Xiangrui | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Fuzzy System for Automotive Fault Diagnosis

    Hamilton, Brennan / Chen, Tie-Qi / Lu, Yi | SAE Technical Papers | 1998
    Schlagwörter: Machine learning

    A Hybrid Classification of Driver’s Style and Skill Using Fully-Connected Deep Neural Networks

    Hu, Hongyu / Liu, Jiarui / Hu, Ruofei | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Hybrid Method for Automotive Entity Recognition

    Manalikandy, Mithun / Sivaraman, Navya K / Koduri, Rajesh | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    A Hybrid System and Method for Estimating State of Charge of a Battery

    Gogate, Aditya / Chakraborty, Debango / Ghivari, Mahesh et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    AI-Based Rotation Aware Detection of Aircraft and Identification of Key Features for Collision Avoidance Systems (SAE Paper 2022-01-0036)

    Kwasniewska, Alicja / MacAllister, Anastacia / Gamba, David et al. | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    AI-Based Virtual Sensing of Gaseous Pollutant Emissions at the Tailpipe of a High-Performance Vehicle

    Brusa, Alessandro / Petrone, Boris / Giovannardi, Emanuele et al. | SAE Technical Papers | 2024
    Schlagwörter: Machine learning

    A Machine Learning Approach for Automating Software Code Review

    Taggarsi, Bhavana Mohan / Kameshwari Prasad Dev, M / Hossain, Shadab | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    A Machine Learning Approach for Hydrogen Internal Combustion (H2ICE) Mixture Preparation

    Jose, Alen / Probst, Daniel / Biware, Mukul | SAE Technical Papers | 2024
    Schlagwörter: Machine learning

    A Machine Learning Approach for Vibration Signal Based Fault Classification on Hydraulic Braking System through C4.5 Decision Tree Classifier and Logistic Model Tree Classifier

    A, Joshuva / Subramaniam, Mohankumar / Selvaraju, Nandakumar et al. | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    A Machine Learning Approach in the Design of Friction Materials for Automotive Applications: Correlation among Composition, Process Parameters and Functional Characteristics

    Portesani, Alberto / Busso, Massimo / Regis, Pierluigi et al. | SAE Technical Papers | 2006
    Schlagwörter: Machine learning

    A Machine Learning Approach to Information Extraction from Cylinder Pressure Sensors

    Bernhardsson, Bo / Henningsson, Maria / Tunestal, Per et al. | SAE Technical Papers | 2012
    Schlagwörter: Machine learning

    A Machine Learning-Genetic Algorithm (ML-GA) Approach for Rapid Optimization Using High-Performance Computing

    Moiz, Ahmed Abdul / Probst, Daniel / Kodavasal, Janardhan et al. | SAE Technical Papers | 2018
    Schlagwörter: Machine learning

    A Machine Learning Modeling Approach for High Pressure Direct Injection Dual Fuel Compressed Natural Gas Engines

    Karpinski-Leydier, Michael / Kirchen, Patrick / Nagamune, Ryozo | SAE Technical Papers | 2020
    Schlagwörter: Machine learning

    A Method of Reporting and Prioritizing Faults for Aircraft Downtime Reduction

    Barkat, Mohammad / N, Pradeep / Karan, Vivek | SAE Technical Papers | 2017
    Schlagwörter: Machine learning

    A Methodology for Multi-Objective Design Optimization (MDO) of Automotive Suspension Systems

    Ganesh, Lingadalu | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    A Multiagency Long Short-Term Model Beamforming Prediction Model for Cellular Vehicle to Everything

    Liu, Sheng / Elangovan, Vivekanandh / Xiang, Weidong | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    A Multi-Axle and Multi-Type Truck Load Identification System for Dynamic Load Identification

    Qi, Fei / Chen, Long / Lu, Xin | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    Analysis and Interpretation of Data-Driven Closure Models for Large Eddy Simulation of Internal Combustion Engine

    Daly, Conor / Schmidt, David / Haghshenas, Majid et al. | SAE Technical Papers | 2021
    Schlagwörter: Machine learning

    Analytic Study of China’s Latest New Energy Vehicle Market Subsidies in Facing of the Carbon Neutrality Goal

    Li, Xinyi / Wan, Yaya / Liao, Yuhong et al. | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    An Analysis of ISO 26262: Machine Learning and Safety in Automotive Software

    Czarnecki, Krzysztof / Salay, Rick / Queiroz, Rodrigo | SAE Technical Papers | 2018
    Schlagwörter: Machine learning

    An Auto-Encoder Based TinyML Approach for Real-Time Anomaly Detection

    Sai Charan, Kovuru | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    An Efficient Machine Learning Algorithm for Valve Fault Detection

    Joshi, Abhishek / Ortiz-Soto, Elliott / Serrano, Joe et al. | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    A Neural Network Based Methodology for Virtual Sensor Development

    Nareid, Helge / Verdejo, Julian / Grimes, Michael | SAE Technical Papers | 2005
    Schlagwörter: Machine learning

    An Evaluation of an Unhealthy Part Identification Using a 0D-1D Diesel Engine Simulation Based Digital Twin

    Sureka, Britant / Saurabh, Shakti | SAE Technical Papers | 2022
    Schlagwörter: Machine learning

    A New Optimal Design of Stable Feedback Control of Two-Wheel System Based on Reinforcement Learning

    Zhu, Xuebin / Yu, Zhenghong | SAE Technical Papers | 2023
    Schlagwörter: Machine learning

    An ML-Based Fleet Management System for Electric Vehicles

    V A, Haseena / M H, Muneer | SAE Technical Papers | 2022
    Schlagwörter: Machine learning