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Guest editorial: special issue on predictive analytics using machine learning

Ali Bou Nassif, Mohammad Azzeh, Shadi Banitaan, Daniel Neagu
2016 Neural computing & applications (Print)  
In "A hybrid grid-GA-based LSSVR learning paradigm for crude oil price forecasting", Yu et al. propose a hybrid learning paradigm integrating least squares support vector regression (LSSVR) with a hybrid  ...  Various degradations may occur in a given engine resulting in changes in the performance of its components.  ...  In ''Classifying component failures of a hybrid electric vehicle fleet based on load spectrum data'', Bergmeir et al. propose a parameter tuning framework that enables the random forest models, formed  ... 
doi:10.1007/s00521-016-2327-3 fatcat:2dqddecrlvfarptlehwbpgqlii

A Review: Prognostics and Health Management in Automotive and Aerospace

Van Duc Nguyen, Marios Kefalas, Kaifeng Yang, Asteris Apostolidis, Markus Olhofer, Steffen Limmer, Thomas B¨ack
2019 International Journal of Prognostics and Health Management  
In general, PHM systems use real-time and historical state information of subsystems and components of the operating systems to provide actionable information, enabling intelligent decision-making for  ...  Every year, a substantial number of papers in this area including theory and practical applications, appear in academic journals, conference proceedings and technical reports.  ...  ACKNOWLEDGEMENTS This work is part of the research programme Smart Industry SI2016 with project name CIMPLO and project number 15465, which is partly financed by the Netherlands Organisation for Scientific  ... 
doi:10.36001/ijphm.2019.v10i2.2730 fatcat:4xe5ylcxy5boxchrna2bggckba

A Review on Emerging Communication and Computational Technologies for Increased Use of Plug-In Electric Vehicles

Vinay Simha Reddy Tappeta, Bhargav Appasani, Suprava Patnaik, Taha Selim Ustun
2022 Energies  
Machine learning and deep learning technologies are being used to manage EV-charging station interactions, estimate the charging behavior, and to use EVs in the load balancing and stability control of  ...  Balancing the load during peak hours, i.e., managing the energy between the grid and vehicle, requires efficient communication protocols, standards, and computational technologies that are essential for  ...  K-nearest neighbors, random forests, and decision trees have been used extensively by many researchers in the EVs domain for load forecasting and energy monitoring.  ... 
doi:10.3390/en15186580 fatcat:vhimwcaiknfebhrfzsdafsimla

Electric Vehicle Batteries: Status and Perspectives of Data-Driven Diagnosis and Prognosis

Jingyuan Zhao, Andrew F. Burke
2022 Batteries  
This paper is concerned with the present status of the information available on the battery with a focus on data-driven diagnostic and prognostic approaches, and how the information would be generated  ...  Mass marketing of battery-electric vehicles (EVs) will require that car buyers have high confidence in the performance, reliability and safety of the battery in their vehicles.  ...  Random forest-based classifier effectively learns the healthy and faulty features from the charge-discharge data.  ... 
doi:10.3390/batteries8100142 fatcat:jqlqkvdpyzhu5bpudpyd4wwonq

2021 Index IEEE Transactions on Industrial Informatics Vol. 17

2021 IEEE Transactions on Industrial Informatics  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  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.  ...  Ali, A., +, TII Sept. 2021 5982-5992 Open Source Algorithm for Smart Charging of Electric Vehicle Fleets.  ... 
doi:10.1109/tii.2021.3138206 fatcat:ulsazxgmpfdmlivigjqgyl7zre

Frequency-dependent Modeling of Generic Honeycomb Networks

Andrea Schaefer, Jutta Hanson, Gerd Balzer
2021 2021 56th International Universities Power Engineering Conference (UPEC)  
He is a fellow of the Royal Academy of Engineering and IEEE.  ...  He has researched Soft-Open-Points for enhanced operation of distribution networks, High Voltage DC for international interconnection and the stability of inverterdominated grids and microgrids.  ...  finding a correspondence between registered consumes for a Battery Electric Vehicle, using a dedicated algorithm, and data available installing a MEMS sensors platform in a scenario which recreates on-road  ... 
doi:10.1109/upec50034.2021.9548165 fatcat:gbknqlpq6fcidm7yp65i5ve6da

Autonomous Vehicles and Intelligent Automation: Applications, Challenges, and Opportunities

Gourav Bathla, Kishor Bhadane, Rahul Kumar Singh, Rajneesh Kumar, Rajanikanth Aluvalu, Rajalakshmi Krishnamurthi, Adarsh Kumar, R. N Thakur, Shakila Basheer, M. Praveen Kumar Reddy
2022 Mobile Information Systems  
In this survey, in-depth analysis of design techniques of intelligent tools and frameworks for AI and IoT-based autonomous vehicles was conducted.  ...  Furthermore, autonomous electric vehicle functionality is also covered with its applications.  ...  Hence, it forms a necessity for the classification of data that uses pattern recognition. Category of data helps in reducing the dataset. e SVM and HOG are widely used for component analysis.  ... 
doi:10.1155/2022/7632892 fatcat:7ffu7l77pngirijr2blvtefhym


2016 Theory, Design, and Applications of Unmanned Aerial Vehicles  
It is believed that drones can play a critical role in identifying and mining the deposits of rare earth elements, which are widely used in electrical and hybrid electrical vehicle parts, infrared lasers  ...  Figure 1 . 1 11 Convergence of load balancing algorithm using Monte Carlo simulation involving multiple unmanned aerial vehicles.  ... 
doi:10.1201/9781315371191-11 fatcat:ojxmcgvlnfcqvcwih27atw5wdu

A Survey of Predictive Maintenance: Systems, Purposes and Approaches [article]

Yongyi Ran, Xin Zhou, Pengfeng Lin, Yonggang Wen, Ruilong Deng
2019 arXiv   pre-print
We make a brief review on the knowledge based and traditional ML based approaches applied in diverse industrial systems or components with a complete list of references, while providing a comprehensive  ...  With the trend of smart manufacturing and development of Internet of Things (IoT), data mining and Artificial Intelligence (AI), etc., PdM is proposed as a novel type of maintenance paradigm to perform  ...  Furthermore, a set of DTs can be trained and assembled to a Random Forest (RF).  ... 
arXiv:1912.07383v1 fatcat:vjunlhidqra7baucyl42ss45iy

The Enabling Technologies for a Quasi-Zero Emissions Commuter Aircraft

Danilo Ciliberti, Pierluigi Della Vecchia, Vittorio Memmolo, Fabrizio Nicolosi, Guido Wortmann, Fabrizio Ricci
2022 Aerospace (Basel)  
At time of writing, there are no certified electric aircraft for passengers' transport.  ...  In fact, it is the opinion of the European Community, which has financed several projects, that advances on the small air transport will be a fundamental step to assess the results and pave the way for  ...  The funders had no rol design of the study; in the collection, analyses, or interpretation of data; in the writing of th script, or in the decision to publish the results.  ... 
doi:10.3390/aerospace9060319 fatcat:hmgtoood7zgntcfqhfn43gtxie

Tackling Climate Change with Machine Learning [article]

David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli (+6 others)
2019 arXiv   pre-print
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help.  ...  Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate.  ...  Foundation and Carnegie Mellon University (SES-00949710), US Department of Energy contract DE-FG02-97ER25308, the Natural Sciences and Engineering Research Council of Canada, and the MIT Media Lab Consortium  ... 
arXiv:1906.05433v2 fatcat:ykmqsivkbfcazaz3wl5f7srula

Electric road vehicles for island communities: A study of the potential for introduction in the Scottish Islands

1991 Transportation Research Part A General  
"State-of-The-Art Assessment of Electric and Hybrid Vehicles" Prepared for the US Department of Energy, Jan 1978, Appendix C (12] House of Lords Select Committee on Science and Technology Electric  ...  "Electric Vehicles in Fleet Service and Prospects for Volume Production" (5] Jones A T, Fleet Advisory Management Services, 1984.  ...  "Energy Utilisation of Electric and Hybrid Vehicles and their Impact on US National Energy Consumption" Int. J. of Vehicle Design, vol. 3, No. 4,1982. Alziew J, Robert J, 1984.  ... 
doi:10.1016/0191-2607(91)90161-i fatcat:n6nymdpvnrhrdjjruynfk5kjqa

2021 Index IEEE Transactions on Automation Science and Engineering Vol. 18

2021 IEEE Transactions on Automation Science and Engineering  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  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.  ...  ., +, TASE Jan. 2021 346-355 Hybrid electric vehicles A Computing Budget Allocation Method for Minimizing EV Charging Cost Using Uncertain Wind Power.  ... 
doi:10.1109/tase.2021.3120615 fatcat:ybfn4kfdvjfipbty7z3mocjjci

Table of Contents

2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
Yao Ponnuthurai Nagaratnam Suganthan A New Random Forest Method for Longitudinal Data Classification Using a Lexicographic Bi-Objective Approach Caio Ribeiro and Alex Freitas .......... 806 Arturo  ...  Fault Detection Using Singular Spectrum Analysis and Kernel Principal Component Analysis Syamala Krishnannair .......... 871 xxiii Design of a Linear Quantum Projection Filter Peng Zhang, Qing  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li

Internet of Things 2.0: Concepts, Applications, and Future Directions

Ian Zhou, Imran Makhdoom, Negin Shariati, Muhammad Ahmad Raza, Rasool Keshavarz, Justin Lipman, Mehran Abolhasan, Abbas Jamalipour
2021 IEEE Access  
Random forest is described in the next part of this subsection. h: Random Forest The random forest is an ensemble learning method based on DT [61] . It consists of multiple DTs.  ...  Advanced spectrum sharing and interference management enable wider coverage area and higher traffic load balance [24] .  ... 
doi:10.1109/access.2021.3078549 fatcat:g5jkc5p6tngpfonbhtsbcjipai
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