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An AdaBoost-Based Intelligent Driving Algorithm for Heavy-Haul Trains

Siyu Wei, Li Zhu, Lijie Chen, Qingqing Lin
2021 Actuators  
Aiming at this unbalanced characteristic, we introduce the classification method in the field of machine learning and design an intelligent driving algorithm for heavy-haul trains.  ...  In this paper, we take the Shuohuang Railway as the research background and analyze the train operation data of SS4G locomotives.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/act10080188 fatcat:7hc5uhuwu5ftlaz4pwa73ejobe

Author Index

2021 2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)  
Bi, Xinjie Visibility Graph based Feature Extraction for Fault Diagnosis of Rolling Bearings [570256] Bin, Jie Optimization Method of Virtual Sand Table Background Server Based on Unity 3D [571175] C  ...  PHM-Nanjing) 42A Feature with Improved Attention An Improved Marginal Index Method to Diagnose Poor Welded Joints of Heavy-haul Railway Non-Invasive Online Condition Monitoring Method for Both SiC MOSFET  ...  with 2nd-Level Relaxation Clustering [570378] Evaluation Method of Rotating Machinery Health State Based on TPE-XGBoost [570379] Xiao, Zhuo A Review of Fault Diagnosis Methods Based on Machine Learning  ... 
doi:10.1109/phm-nanjing52125.2021.9612757 fatcat:h4xp5wbdvjdpvmsri2dktwupbi

Supervised Machine Learning Approach for Detecting Missing Clamps in Rail Fastening System from Differential Eddy Current Measurements

Praneeth Chandran, Florian Thierry, Johan Odelius, Stephen M. Famurewa, Håkan Lind, Matti Rantatalo
2021 Applied Sciences  
The data required for the study was collected from field measurements carried out along a heavy haul railway line in the north of Sweden, using the train-based differential eddy current sensor system.  ...  This study analyses the performance of a machine learning algorithm for detecting and analysing missing clamps within the fastening system, measured using a train-based differential eddy current sensor  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app11094018 doaj:2e39ee3b80e24b7194deb821fd39e7f3 fatcat:m7nhcu4inbf4xjwufbzizfpe5i

Internet of things for high-speed railways

Guidong Zhong, Ke Xiong, Zhangdui Zhong, Bo Ai
2021 Intelligent and Converged Networks  
Based on these concepts, a system architecture of the HSR IoT is proposed to expand the in-depth applications of IoT in various fields of the HSR industry.  ...  As a new generation of application infrastructure and strategic emerging technologies, the internet of things (IoT) is an inevitable trend to be integrated into the rapid development of high-speed railways  ...  Acknowledgment This work was supported in part by the US Department of Commerce (No. BS123456).  ... 
doi:10.23919/icn.2021.0005 fatcat:7ymtejvsrrcv5dtzqwawjnphvq

Towards Integrating Intelligence and Programmability in Open Radio Access Networks: A Comprehensive Survey

Azadeh Arnaz, Justin Lipman, Mehran Abolhasan, Matti Hiltunen
2022 IEEE Access  
the compatibility of products with the RAN ecosystem.  ...  The traditional approach of building end-to-end RAN solutions by only one vendor hampers the speed of innovation-furthermore, the lack of a standard approach to implementing artificial intelligence complicates  ...  As a result, it reduces the cost of pre-processing steps in machine learning. However, the range of problems that this learning method can solve is minimal compared to the supervised learning method.  ... 
doi:10.1109/access.2022.3183989 fatcat:kbg77alhvrhlrnznmxg6zvq6fq

A New Method for Inverter Diagnosis of Electric Locomotive Using Adversarial Neural Networks

Yingchun Shi, Chunyang Chen, Yu Luo, Fang Liu
2022 Security and Communication Networks  
Moreover, at the data level, this article compares and analyzes three methods of data expansion based on single-sample processing, data expansion based on image front and background separation, and data  ...  Finally, this article uses the LBP operator to extract the image texture features to distinguish and detect the different shapes of the rotor windings and build an intelligent system to verify the effect  ...  Adaptability: literature [11] used a combination of wavelet analysis and neural network diagnosis method for the rectifier fault of HXDl heavy-haul freight locomotive.  ... 
doi:10.1155/2022/5606328 fatcat:fj3nxib7dvdancpu76llor3idy

Towards Autonomous Mining via Intelligent Excavators

Hooman Shariati, Anuar Yeraliyev, Burhan Terai, Shahram Tafazoli, Mahdi Ramezani
2019 Computer Vision and Pattern Recognition  
Finally, our work on detecting the types of objects encountered in a mining equipment could be used as a first step in developing a perception module that could provide autonomous excavators with the required  ...  Our solution (intelligent excavator) provides complete monitoring solution for excavators that relies on deep neural networks to produce accurate, actionable data for mine.  ...  Perception refers to any software and machine learning modules that is responsible for acquiring raw sensor data from on vehicle sensors such as cameras, lidar, and radar, and converting this raw data  ... 
dblp:conf/cvpr/ShariatiYTTR19 fatcat:q3m7u7tgpzgrzekqsocgrhkh4y

Applications of Machine Learning in Networking: A Survey of Current Issues and Future Challenges

M. A. Ridwan, N. A. M. Radzi, F. Abdullah, Y. E. Jalil
2021 IEEE Access  
A review of the recent literature reveals extensive opportunities for researchers to exploit the advantages of ML in solving complex performance issues in a network, especially with the advancement of  ...  Machine learning (ML) has recently been applied to solve complex problems in many fields, including finance, health care, and business.  ...  Given the potential of ML, an intelligent caching of data at the base station allows a significant offloading of heavy traffic from the network backhaul.  ... 
doi:10.1109/access.2021.3069210 fatcat:4i7vykwabbattm5uh3mgsdmhvi

Table of Contents

2021 2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing)  
Train Operation System [570315]Ziqi Wang, Wei Shangguan, Cong Peng and Hongyu Song A Simulation- based Study of the Effects of Incomplete Data on Lifetime Distribution Estimation due to Censorship [  ...  , Hongyang Zhao and Gang Niu An Improved Marginal Index Method to Diagnose Poor Welded Joints of Heavy-haul Railway [571143] Binghuan Xiao, Xuegeng Mao, Jinzhao Liu, Liubin Niu, Xiaodi Xu and Maoxuan Zhang  ... 
doi:10.1109/phm-nanjing52125.2021.9612743 fatcat:5wsvymyibvahpek6tpeqib2eki

Application of Machine Learning in Wireless Networks: Key Techniques and Open Issues [article]

Yaohua Sun, Mugen Peng, Yangcheng Zhou, Yuzhe Huang, Shiwen Mao
2019 arXiv   pre-print
As a key technique for enabling artificial intelligence, machine learning (ML) is capable of solving complex problems without explicit programming.  ...  also summarized together with their performance comparison with ML based approaches, based on which the motivations of surveyed literatures to adopt ML are clarified.  ...  By avoiding training learning models from scratch, the learning process in new environments can be speeded up, and the ML algorithm can have a good performance even with a small amount of training data  ... 
arXiv:1809.08707v2 fatcat:6tnzliwthfehrpuxpmm45hs4vq

Proceedings of The International Research Education & Training Center [article]

Namig Isazade
2021 Zenodo  
Proceedings of The International Research Education & Training Center  ...  With Artificial intelligence (AI) and Machine Learning (ML) methods, the machine can be controlled from the internet according to specific rules.  ...  After that, the traditional static analysis used a data method based on machine learning, data mining [10] [11] [12] [13] . 3.  ... 
doi:10.5281/zenodo.5502124 fatcat:j5vvdb3j5nemvpo4splz4n7ziq

Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data

Rune Prytz, Sławomir Nowaczyk, Thorsteinn Rögnvaldsson, Stefan Byttner
2015 Engineering applications of artificial intelligence  
It is shown on a large data set from heavy duty trucks in normal operation how this can be done and generate a profit.  ...  Methods and results are presented for applying supervised machine learning techniques to the task of predicting the need for repairs of air compressors in commercial trucks and buses.  ...  Independent data sets for training and testing A central assumption in machine learning (and statistics) it that of independent and identically distributed (IID) data.  ... 
doi:10.1016/j.engappai.2015.02.009 fatcat:oeezxsy3zrhwpif33p7sc6wtui

An Overview on Application of Machine Learning Techniques in Optical Networks [article]

Francesco Musumeci, Cristina Rottondi, Avishek Nag, Irene Macaluso, Darko Zibar, Marco Ruffini, Massimo Tornatore
2018 arXiv   pre-print
Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration  ...  Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data.  ...  INTRODUCTION Machine learning (ML) is a branch of Artificial Intelligence that pushes forward the idea that, by giving access to the right data, machines can learn by themselves how to solve a specific  ... 
arXiv:1803.07976v4 fatcat:rhzumocnrzfxpismbpkjejytfm

An Overview on Application of Machine Learning Techniques in Optical Networks

Francesco Musumeci, Cristina Rottondi, Avishek Nag, Irene Macaluso, Darko Zibar, Marco Ruffini, Massimo Tornatore
2018 IEEE Communications Surveys and Tutorials  
Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration  ...  Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data.  ...  INTRODUCTION Machine learning (ML) is a branch of Artificial Intelligence that pushes forward the idea that, by giving access to the right data, machines can learn by themselves how to solve a specific  ... 
doi:10.1109/comst.2018.2880039 fatcat:ql662vgph5hjdejxtl5yvdysom

2021 Index IEEE Transactions on Industrial Informatics Vol. 17

2021 IEEE Transactions on Industrial Informatics  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TII May 2021 3069-3078 Multidimensional Feature Fusion and Ensemble Learning-Based Fault Diagnosis for the Braking System of Heavy-Haul Train.  ...  ., +, TII Jan. 2021 659-666 Multidimensional Feature Fusion and Ensemble Learning-Based Fault Diag-nosis for the Braking System of Heavy-Haul Train.  ... 
doi:10.1109/tii.2021.3138206 fatcat:ulsazxgmpfdmlivigjqgyl7zre
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