Semantic sensor data integration for talent development via hybrid multi‐objective evolutionary algorithm

In this work, we propose a new hybrid Multi‐Objective Evolutionary Algorithm (hMOEA) specifically designed for semantic sensor data integration, targeting talent development within the burgeoning field of the Semantic Internet of Things (SIoT). Our approach synergizes the capabilities of Multi‐Objec...

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Published in:Internet technology letters Vol. 8; no. 2
Main Authors: Luo, Fang, Yang, Ya‐Juan, Geng, Yu‐Cheng
Format: Journal Article
Language:English
Published: Chichester, UK John Wiley & Sons, Ltd 01.03.2025
Subjects:
evolutionary
multi‐objective
ontology
semantic
talent
ISSN:2476-1508, 2476-1508
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Abstract In this work, we propose a new hybrid Multi‐Objective Evolutionary Algorithm (hMOEA) specifically designed for semantic sensor data integration, targeting talent development within the burgeoning field of the Semantic Internet of Things (SIoT). Our approach synergizes the capabilities of Multi‐Objective Particle Swarm Optimization and Genetic Algorithms to tackle the sophisticated challenges inherent in Sensor Ontology Matching (SOM). This innovative hMOEA framework is adapt at discerning precise semantic correlations among diverse ontologies, thereby facilitating seamless interoperability and enhancing the functionality of IoT applications. Central to our contributions are the development of an advanced multi‐objective optimization model that underpins the SOM process, the implementation of the hMOEA framework which sets a new benchmark for accurate semantic sensor data integration, and the rigorous validation of hMOEA's superiority through extensive testing in varied real‐world SOM scenarios. This research not only marks a significant advancement in SOM but also highlights the critical role of cutting‐edge SOM methodologies in educational curricula, for example, the new business subject education proposed by China in recent years, aimed at equipping future professionals with the necessary skills to innovate and lead in the SIoT and SW domains.
AbstractList In this work, we propose a new hybrid Multi‐Objective Evolutionary Algorithm (hMOEA) specifically designed for semantic sensor data integration, targeting talent development within the burgeoning field of the Semantic Internet of Things (SIoT). Our approach synergizes the capabilities of Multi‐Objective Particle Swarm Optimization and Genetic Algorithms to tackle the sophisticated challenges inherent in Sensor Ontology Matching (SOM). This innovative hMOEA framework is adapt at discerning precise semantic correlations among diverse ontologies, thereby facilitating seamless interoperability and enhancing the functionality of IoT applications. Central to our contributions are the development of an advanced multi‐objective optimization model that underpins the SOM process, the implementation of the hMOEA framework which sets a new benchmark for accurate semantic sensor data integration, and the rigorous validation of hMOEA's superiority through extensive testing in varied real‐world SOM scenarios. This research not only marks a significant advancement in SOM but also highlights the critical role of cutting‐edge SOM methodologies in educational curricula, for example, the new business subject education proposed by China in recent years, aimed at equipping future professionals with the necessary skills to innovate and lead in the SIoT and SW domains.
Author Luo, Fang
Geng, Yu‐Cheng
Yang, Ya‐Juan
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References 1989; 40
2023; 40
2017; 8
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2023; 132
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References_xml – volume: 20
  start-page: 2056
  issue: 7
  year: 2020
  article-title: Optimizing sensor ontology alignment through compact co‐firefly algorithm
  publication-title: Sensors
– volume: 9
  start-page: 435
  issue: 1
  year: 2023
  end-page: 462
  article-title: A multi‐objective particle swarm optimization with density and distribution‐based competitive mechanism for sensor ontology meta‐matching
  publication-title: Complex Intell Syst
– volume: 21
  start-page: 24570
  issue: 21
  year: 2021
  end-page: 24578
  article-title: Matching sensor ontologies with multi‐context similarity measure and parallel compact differential evolution algorithm
  publication-title: IEEE Sens J
– volume: 6
  start-page: 182
  issue: 2
  year: 2002
  end-page: 197
  article-title: A fast and elitist multiobjective genetic algorithm: NSGA‐II
  publication-title: IEEE Trans Evol Comput
– volume: 132
  start-page: 190
  year: 2023
  end-page: 198
  article-title: Complex ontology alignment for autonomous systems via the compact co‐evolutionary brain storm optimization algorithm
  publication-title: ISA Trans
– start-page: 1
  year: 2024
  end-page: 13
  article-title: Similarity feature construction for semantic sensor ontology integration via light genetic programming
  publication-title: IEEE Internet Things J
– start-page: 91
  year: 2016
  end-page: 95
– volume: 13
  start-page: 12581
  issue: 9
  year: 2013
  end-page: 12604
  article-title: Ontology alignment architecture for semantic sensor web integration
  publication-title: Sensors
– volume: 17
  start-page: 25
  year: 2012
  end-page: 32
  article-title: The SSN ontology of the W3C semantic sensor network incubator group
  publication-title: J Web Semant
– volume: 56
  start-page: 1
  year: 2019
  end-page: 10
  article-title: SOSA: a lightweight ontology for sensors, observations, samples, and actuators
  publication-title: J Web Semant
– volume: 40
  issue: 4
  year: 2023
  article-title: Generative adversarial learning for optimizing ontology alignment
  publication-title: Expert Syst
– volume: 8
  start-page: 766
  issue: 4
  year: 2017
  end-page: 773
  article-title: Using artificial bee colony algorithm for optimizing ontology alignment
  publication-title: J Inf Hiding Multim Signal Process
– volume: 40
  start-page: 145
  issue: 3
  year: 1989
  end-page: 151
  article-title: Recall‐precision trade‐off: a derivation
  publication-title: J Am Soc Inf Sci
– volume: 2021
  start-page: 1
  year: 2021
  end-page: 11
  article-title: Matching sensor ontologies with simulated annealing particle swarm optimization
  publication-title: Mob Inf Syst
– start-page: 3
  year: 2017
  end-page: 36
– volume: 48
  start-page: 25
  year: 2019
  end-page: 30
  article-title: Using compact evolutionary tabu search algorithm for matching sensor ontologies
  publication-title: Swarm Evol Comput
– start-page: 90
  year: 2016
  end-page: 97
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Snippet In this work, we propose a new hybrid Multi‐Objective Evolutionary Algorithm (hMOEA) specifically designed for semantic sensor data integration, targeting...
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SourceType Publisher
SubjectTerms evolutionary
multi‐objective
ontology
semantic
talent
Title Semantic sensor data integration for talent development via hybrid multi‐objective evolutionary algorithm
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