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Clustering-Based Intelligent Ev Charging Station Selection Using Dynamic User Requests and Station Status

https://doi.org/10.2139/ssrn.5274646
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Outgoing claims: the papers this work cites, builds on, or argues with.

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RPRA: Reputation-based prioritization and resource allocation leveraging predictive analytics and vehicular fog computing
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Multi-agent deep reinforcement learning approach for EV charging scheduling in a smart grid
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Data-driven equitable placement for electric vehicle charging stations: Case study San Francisco
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TSM: Temporal segmentation and modules-based computation offloading using predictive analytics and NR-V2X
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Electric vehicles charging infrastructure framework using internet of things
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Clustering-based optimal operation of charging stations under high penetration of electric vehicles
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A traffic-aware electric vehicle charging management system for smart cities
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Artificial Intelligence and Machine Learning as key enablers for V2X communications: A comprehensive survey
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Optimal load management strategy for large electric vehicle charging stations with undersized charger clusters
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Electric vehicle charging assistive system using internet of electric vehicles
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Electric vehicles charging infrastructure planning: a review
inferredcites →https://doi.org/10.1109/access.2018.2879644openalex-snapshot
EVP-STC: Emergency Vehicle Priority and Self-Organising Traffic Control at Intersections Using Internet-of-Things Platform
inferredcites →https://doi.org/10.1109/access.2024.3487839openalex-snapshot
A Fuzzy-Multi Attribute Decision Making Scheme for Efficient User-Centric EV Charging Station Selection
inferredcites →https://doi.org/10.1109/iccc51575.2020.9344906openalex-snapshot
Analysis on Charging Safety and Optimization of Electric Vehicles
inferredcites →https://doi.org/10.1109/icces48766.2020.9137937openalex-snapshot
IoT Based Charging Slot Locator at Charging Station
inferredcites →https://doi.org/10.1109/icpeev58650.2023.10391930openalex-snapshot
IoT enabled E-Vehicle Charging System with Battery Monitoring and Charge Scheduling
inferredcites →https://doi.org/10.1109/iemecon53809.2021.9689147openalex-snapshot
Electric vehicle charging station integration with IOT enabled device
inferredcites →https://doi.org/10.1109/incoft55651.2022.10094520openalex-snapshot
Reservation System for Charging Electric Vehicles
inferredcites →https://doi.org/10.1109/iscv60512.2024.10620096openalex-snapshot
Dynamic Selection of Electric Vehicle Charging Stations Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/mc.2024.3350871openalex-snapshot
Charging Support Communication System Based on Vehicle-to-Vehicle Communication for Electric Vehicles
inferredcites →https://doi.org/10.1109/mce.2020.2985656openalex-snapshot
Smart Station Search Assistance for Electric Vehicle—A Step Toward Smart City
inferredcites →https://doi.org/10.1109/surv.2014.020614.00115openalex-snapshot
Stochastic Information Management in Smart Grid
inferredcites →https://doi.org/10.1109/tits.2020.3044890openalex-snapshot
BlockEV: Efficient and Secure Charging Station Selection for Electric Vehicles
inferredcites →https://doi.org/10.1109/tits.2022.3153122openalex-snapshot
VP-CAST: Velocity and Position-Based Broadcast Suppression for VANETs
inferredcites →https://doi.org/10.1109/tits.2024.3379469openalex-snapshot
A User-Preference-Based Charging Station Recommendation for Electric Vehicles
inferredcites →https://doi.org/10.1109/tsmc.2019.2917149openalex-snapshot
Toward Pre-Empted EV Charging Recommendation Through V2V-Based Reservation System
inferredcites →https://doi.org/10.1109/tste.2022.3232594openalex-snapshot
A Data-driven Agent-based Planning Strategy of Fast-Charging Stations for Electric Vehicles
inferredcites →https://doi.org/10.1145/3534678.3539154openalex-snapshot
Reinforcement Learning-based Placement of Charging Stations in Urban Road Networks
inferredcites →https://doi.org/10.1145/3647444.3652445openalex-snapshot
Smart Charging for Electric Vehicles: A Meta-Heuristic Analysis
inferredcites →https://doi.org/10.11591/eei.v9i1.1564openalex-snapshot
System architecture to select the charging station by optimizing the travel time considering the destination of electric vehicle drivers in smart cities
inferredcites →https://doi.org/10.11591/ijece.v13i3.pp3266-3280openalex-snapshot
Initial location selection of electric vehicles charging infrastructure in urban city through clustering algorithm
inferredcites →https://doi.org/10.1504/ijehv.2020.10035270openalex-snapshot
Automatic discovery and selection of most qualified electric vehicle charging station
inferredcites →https://doi.org/10.1515/ijeeps-2023-0124openalex-snapshot
Optimal ranking-based charging station selection for electric vehicles
inferredcites →https://doi.org/10.3390/cleantechnol2010001openalex-snapshot
Electrical Vehicles: Current State of the Art, Future Challenges, and Perspectives
inferredcites →https://doi.org/10.3390/en15249471openalex-snapshot
Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging
inferredcites →https://doi.org/10.3390/fi11040094openalex-snapshot
A Review of Machine Learning and IoT in Smart Transportation
inferredcites →https://doi.org/10.3390/s19133015openalex-snapshot
Barrier Access Control Using Sensors Platform and Vehicle License Plate Characters Recognition
inferredcites →https://doi.org/10.3390/wevj15020067openalex-snapshot
Optimizing Electric Vehicle Charging Recommendation in Smart Cities: A Multi-Agent Reinforcement Learning Approach
inferredcites →https://doi.org/10.70356/josapen.v2i1.25openalex-snapshot
Editorial: Smart Parking Management System Using Artificial Intelligence
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V2I-VTL: IoT-Enabled adaptive traffic light controller and emission reduction at intersection
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.