Analysis of Semantic Web Ontologies using K-Means Clustering
Deepak Fernando
Corresponding
Islamic University of Technology
Arjun Rahman
University of Cape Town
Abstract
The need for sustainable and low-cost solutions has focused attention on semantic web ontologies within embedded control systems. A mathematical model is developed and solved using k-means clustering to capture the essential features of the problem. The analysis shows that semantic web ontologies rises sharply when the load exceeds 3 times the rated value. The results underline the importance of accounting for local conditions in engineering design.
Keywords:
semantic web ontologiesk-means clusteringparticle swarm optimisationMIMO systemswireless sensor networks
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