Search Results - (( based applications clustering algorithm ) OR ( mobile application a algorithm ))*
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Adaptive fault tolerant checkpointing algorithm for cluster based mobile Ad Hoc networks
Published 2015“…This has made possible to create a distributed mobile computing application and has also brought several new challenges in distributed algorithm design. …”
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Proceeding Paper -
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Cauchy Density-based Algorithm for VANETs Clustering in 3D Road Environments
Published 2022“…In addition, a clustering algorithm that defines mobility vector and uses Cauchy-based density for enabling adding vehicles to their respective clusters. …”
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Energy Balancing Through Cluster Head Selection Using K-Theorem in Homogeneous Wireless Sensor Networks
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Conference or Workshop Item -
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Enhanced weight-based clustering algorithm to provide reliable delivery for VANET safety applications
Published 2019“…In this study, enhanced weight-based clustering algorithm (EWCA) was developed to address these challenges. …”
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An energy based cluster head selection unequal clustering algorithm with dual sink (ECH-DUAL) for continuous monitoring applications in wireless sensor networks
Published 2018“…In this work, an energy based cluster head selection unequal clustering algorithm (ECH-DUAL) using dual (static and mobile) sink is proposed. …”
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A green clustering protocol for mobile sensor network using particle swarm optimization
Published 2016“…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
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A green clustering protocol for mobile sensor network using particle swarm optimization
Published 2016“…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…The problems with the K-Means algorithm concern the selection of a suitable number of clusters, the creation of a highly reliable cluster, and achieving high similarity within a cluster. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…In the online phase, the stream clustering algorithm for trajectories based on the lifespan of the cluster is proposed (CC_TRS) to overcome the limitations of the time window technique. …”
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Thesis -
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Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Efficient Clustering Method
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Citation Index Journal -
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Cauchy density-based algorithm for VANETs clustering in 3D road environments
Published 2022“…This paper attempts to solve the problem of VANETs in 3D road environments using a centralized clustering technique to develop a Cauchy density model. …”
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Energy-efficient data transmission with clustering and compressive sensing in wireless sensor networks / Mukil Alagirisamy
Published 2020“…In the extended ECH-DUAL algorithm in addition to dual sink a new cluster head selection method is proposed for unequal clustering. …”
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A machine learning approach to tourism recommendations system
Published 2025“…Model with the highest accuracy will be integrated into a tourism recommendation mobile application. A high portability and mobility mobile application will be developed by using React Native, and the dataset used in developing will be obtained from Google API. …”
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Final Year Project / Dissertation / Thesis -
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Reliable Fuzzy-Based Multi-Path Routing Protocol Based on Whale Optimization Algorithm to Improve QOS in 5G Networks for IOMT Applications
Published 2024“…To function in the linked ecosystem, IoMT based on 5G is anticipated to have a diversity of energy and mobility. …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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