Towards the design of a particle swarm optimization ontology for object classification

This article proposes an ontology blueprint inspired by key components of the particle swarm system to address the object classification problem. The identified key components particle, swarm, search space, goal, environment and fitness measures were independently evaluated based on their sub-entiti...

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Main Authors: Nyaradzo Alice Tsedura, Ernest Bhero, Colin Chibaya
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Array
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2590005625000761
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author Nyaradzo Alice Tsedura
Ernest Bhero
Colin Chibaya
author_facet Nyaradzo Alice Tsedura
Ernest Bhero
Colin Chibaya
author_sort Nyaradzo Alice Tsedura
collection DOAJ
description This article proposes an ontology blueprint inspired by key components of the particle swarm system to address the object classification problem. The identified key components particle, swarm, search space, goal, environment and fitness measures were independently evaluated based on their sub-entities, relationships, data flow and storage. These unit designs were integrated into a comprehensive particle swarm system ontology. A technology assessment model, in the form of a questionnaire, was distributed to 15 software engineering experts to evaluate the ontology based on 10 metrics, including completeness, correctness, usefulness and scalability. Results showed that 88 % of responses rated the designs as good, while 12 % found them to be average or poor. These findings confirm the proposed ontology designs as valid, with potential for further refinement based on expert feedback.
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spelling doaj-art-ea0defae67d14ae8a90bf5b94efd300a2025-08-20T03:16:57ZengElsevierArray2590-00562025-09-012710044910.1016/j.array.2025.100449Towards the design of a particle swarm optimization ontology for object classificationNyaradzo Alice Tsedura0Ernest Bhero1Colin Chibaya2College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban, South Africa; Corresponding author.College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban, South AfricaFaculty of Natural and Applied Sciences, Sol Plaatje University, Kimberly, South AfricaThis article proposes an ontology blueprint inspired by key components of the particle swarm system to address the object classification problem. The identified key components particle, swarm, search space, goal, environment and fitness measures were independently evaluated based on their sub-entities, relationships, data flow and storage. These unit designs were integrated into a comprehensive particle swarm system ontology. A technology assessment model, in the form of a questionnaire, was distributed to 15 software engineering experts to evaluate the ontology based on 10 metrics, including completeness, correctness, usefulness and scalability. Results showed that 88 % of responses rated the designs as good, while 12 % found them to be average or poor. These findings confirm the proposed ontology designs as valid, with potential for further refinement based on expert feedback.http://www.sciencedirect.com/science/article/pii/S2590005625000761Scoping reviewOntologyObject classificationParticle swarm system
spellingShingle Nyaradzo Alice Tsedura
Ernest Bhero
Colin Chibaya
Towards the design of a particle swarm optimization ontology for object classification
Array
Scoping review
Ontology
Object classification
Particle swarm system
title Towards the design of a particle swarm optimization ontology for object classification
title_full Towards the design of a particle swarm optimization ontology for object classification
title_fullStr Towards the design of a particle swarm optimization ontology for object classification
title_full_unstemmed Towards the design of a particle swarm optimization ontology for object classification
title_short Towards the design of a particle swarm optimization ontology for object classification
title_sort towards the design of a particle swarm optimization ontology for object classification
topic Scoping review
Ontology
Object classification
Particle swarm system
url http://www.sciencedirect.com/science/article/pii/S2590005625000761
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