Towards the design of a particle swarm optimization ontology for object classification - Nyaradzo Alice Tsedura; Ernest Bhero; Colin Chibaya (Array)
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.