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Machine learning‐based clustering protocols for Internet of Things networks: An overview
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Outgoing claims: the papers this work cites, builds on, or argues with.
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A survey on application of machine learning for Internet of Things
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Wireless underground sensor networks: Research challenges
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inferredcites →https://doi.org/10.1016/j.asoc.2020.106275openalex-snapshot
Fuzzy neural networks and neuro-fuzzy networks: A review the main techniques and applications used in the literature
inferredcites →https://doi.org/10.1016/j.bushor.2015.03.008openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.comcom.2020.10.023openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.comcom.2021.07.014openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.comnet.2019.01.024openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.comnet.2020.107376openalex-snapshot
Clustering objectives in wireless sensor networks: A survey and research direction analysis
inferredcites →https://doi.org/10.1016/j.cosrev.2020.100284openalex-snapshot
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Strategies based on various aspects of clustering in wireless sensor networks using classical, optimization and machine learning techniques: Review, taxonomy, research findings, challenges and future directions
inferredcites →https://doi.org/10.1016/j.dcan.2017.10.002openalex-snapshot
Machine learning for internet of things data analysis: a survey
inferredcites →https://doi.org/10.1016/j.jii.2020.100156openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.jnca.2020.102630openalex-snapshot
Machine learning based solutions for security of Internet of Things (IoT): A survey
inferredcites →https://doi.org/10.1016/j.measurement.2021.108974openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.suscom.2017.08.001openalex-snapshot
An optimal clustering mechanism based on Fuzzy-C means for wireless sensor networks
inferredcites →https://doi.org/10.1016/j.suscom.2019.02.003openalex-snapshot
Scalable and sustainable wireless sensor networks for agricultural application of Internet of things using fuzzy c-means algorithm
inferredcites →https://doi.org/10.1049/iet-com.2018.5546openalex-snapshot
EEFCM‐DE: energy‐efficient clustering based on fuzzy C means and differential evolution algorithm in WSNs
inferredcites →https://doi.org/10.1080/14488388.2020.1811454openalex-snapshot
Energy-efficient density-based Fuzzy C-means clustering in WSN for smart grids
inferredcites →https://doi.org/10.1108/sr-06-2016-0104openalex-snapshot
A survey on clustering routing protocols in wireless sensor networks
inferredcites →https://doi.org/10.1109/5326.704563openalex-snapshot
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inferredcites →https://doi.org/10.1109/access.2019.2916648openalex-snapshot
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges
inferredcites →https://doi.org/10.1109/access.2021.3063097openalex-snapshot
An Unequally Clustered Multi-hop Routing Protocol Based on Fuzzy Logic for Wireless Sensor Networks
inferredcites →https://doi.org/10.1109/access.2021.3069455openalex-snapshot
T2FL-PSO: Type-2 Fuzzy Logic-Based Particle Swarm Optimization Algorithm Used to Maximize the Lifetime of Internet of Things
inferredcites →https://doi.org/10.1109/access.2021.3092509openalex-snapshot
Towards Energy Efficient Clustering in Wireless Sensor Networks: A Comprehensive Review
inferredcites →https://doi.org/10.1109/adprl.2011.5967372openalex-snapshot
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inferredcites →https://doi.org/10.1109/apwimob51111.2021.9435236openalex-snapshot
Type-2 Fuzzy Logic Based Energy-Efficient Cluster Head Election for Multi-Hop Wireless Sensor Networks
inferredcites →https://doi.org/10.1109/cc.2014.6969789openalex-snapshot
An overview of Internet of Vehicles
inferredcites →https://doi.org/10.1109/ccgrid.2019.00077openalex-snapshot
Deep Reinforcement Learning for IoT Network Dynamic Clustering in Edge Computing
inferredcites →https://doi.org/10.1109/ccis.2012.6664541openalex-snapshot
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inferredcites →https://doi.org/10.1109/comapp.2018.8460440openalex-snapshot
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inferredcites →https://doi.org/10.1109/comst.2018.2844341openalex-snapshot
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inferredcites →https://doi.org/10.1109/dsmp.2018.8478538openalex-snapshot
Energy Efficient Clustering Protocol for Heterogeneous Wireless Sensor Network: A Hybrid Approach Using GA and K-means
inferredcites →https://doi.org/10.1109/hpcs.2018.00116openalex-snapshot
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inferredcites →https://doi.org/10.1109/icccnt49239.2020.9225420openalex-snapshot
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inferredcites →https://doi.org/10.1109/icdsba.2018.00049openalex-snapshot
A Survey on Clustering Approaches for Wireless Sensor Networks
inferredcites →https://doi.org/10.1109/iceca.2018.8474875openalex-snapshot
Modified EECPK-means mid-point algorithm for enhancing network life expactancy in WSN
inferredcites →https://doi.org/10.1109/icengtechnol.2017.8308186openalex-snapshot
Understanding of a convolutional neural network
inferredcites →https://doi.org/10.1109/iciafs.2008.4783999openalex-snapshot
Algorithms for Node Clustering in Wireless Sensor Networks: A Survey
inferredcites →https://doi.org/10.1109/icmnwc52512.2021.9688363openalex-snapshot
Energy Efficiency Random Forest Classification based Data Mustering in Wireless Sensor Networks
inferredcites →https://doi.org/10.1109/icoin.2018.8343195openalex-snapshot
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inferredcites →https://doi.org/10.1109/ict52184.2021.9511518openalex-snapshot
EACA: An Energy Aware Clustering Algorithm for Wireless IoT Sensors
inferredcites →https://doi.org/10.1109/isps.2018.8379004openalex-snapshot
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inferredcites →https://doi.org/10.1109/iwcmc48107.2020.9148077openalex-snapshot
Fuzzy C-Means based Clustering Algorithm in WSNs for IoT Applications
inferredcites →https://doi.org/10.1109/jiot.2014.2337336openalex-snapshot
A Vision of IoT: Applications, Challenges, and Opportunities With China Perspective
inferredcites →https://doi.org/10.1109/jiot.2016.2615180openalex-snapshot
IoT Middleware: A Survey on Issues and Enabling technologies
inferredcites →https://doi.org/10.1109/jiot.2017.2683200openalex-snapshot
A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications
inferredcites →https://doi.org/10.1109/jiot.2017.2726014openalex-snapshot
A Survey of Clustering Techniques in WSNs and Consideration of the Challenges of Applying Such to 5G IoT Scenarios
inferredcites →https://doi.org/10.1109/jiot.2017.2773600openalex-snapshot
Context-Aware Computing, Learning, and Big Data in Internet of Things: A Survey
inferredcites →https://doi.org/10.1109/jiot.2018.2846040openalex-snapshot
Securing the Internet of Things in the Age of Machine Learning and Software-Defined Networking
inferredcites →https://doi.org/10.1109/jiot.2019.2893866openalex-snapshot
From Cloud Down to Things: An Overview of Machine Learning in Internet of Things
inferredcites →https://doi.org/10.1109/jiot.2020.3031272openalex-snapshot
Improved Soft- k -Means Clustering Algorithm for Balancing Energy Consumption in Wireless Sensor Networks
inferredcites →https://doi.org/10.1109/jsen.2020.2969697openalex-snapshot
Fuzzy Logic Based Effective Clustering of Homogeneous Wireless Sensor Networks for Mobile Sink
inferredcites →https://doi.org/10.1109/jsen.2021.3054943openalex-snapshot
DEKCS: A Dynamic Clustering Protocol to Prolong Underwater Sensor Networks
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Deep Learning-Based Security Behaviour Analysis in IoT Environments: A Survey
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Clustered chain founded on ant colony optimization energy efficient routing scheme for under-water wireless sensor networks
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Spectral partitioning and fuzzy C-means based clustering algorithm for big data wireless sensor networks
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Energy Efficient Algorithm for Wireless Sensor Network using Fuzzy C-Means Clustering
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Challenges in Wireless Body Area Network
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Energy Efficient Cluster based Routing Protocol with Secure IDS for IoT Assisted Heterogeneous WSN
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Secure cluster-based data aggregation in wireless sensor networks with aid of ECC
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A Fuzzy-logic Based Energy-efficient Clustering Algorithm for the Wireless Sensor Networks
inferredcites →https://doi.org/10.3233/apc210129openalex-snapshot
Energy Efficient Clustering Technique for VANET
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An intelligent low power consumption routing protocol to extend the lifetime of wireless sensor networks based on fuzzy C-Means++ clustering algorithm
inferredcites →https://doi.org/10.3233/jifs-201633openalex-snapshot
Trusted energy aware cluster based routing using fuzzy logic for WSN in IoT
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Machine Learning in Wireless Sensor Networks for Smart Cities: A Survey
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A State-of-the-Art Survey on Deep Learning Theory and Architectures
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Optimized Clustering Algorithms for Large Wireless Sensor Networks: A Review
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Energy-Efficient Fuzzy-Logic-Based Clustering Technique for Hierarchical Routing Protocols in Wireless Sensor Networks
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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