EHIMWENMA, Kennedy E., CROWTHER, Paul and BEER, Martin (2016). A system of serial computation for classified rules prediction in non-regular ontology trees. International journal of artificial intelligence and applications, 7 (2), 23-35.
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Abstract
Objects or structures that are regular take uniform dimensions. Based on the concepts of regular models, our previous research work has developed a system of a regular ontology that models learning structures in a multiagent system for uniform pre-assessments in a learning environment. This regular ontology has led to the modelling of a classified rules learning algorithm that predicts the actual number of rules needed for inductive learning processes and decision making in a multiagent system. But not all processes or models are regular. Thus this paper presents a system of polynomial equation that can estimate and predict the required number of rules of a non-regular ontology model given some defined parameters.
Item Type: | Article |
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Research Institute, Centre or Group - Does NOT include content added after October 2018: | Cultural Communication and Computing Research Institute > Communication and Computing Research Centre |
Departments - Does NOT include content added after October 2018: | Faculty of Science, Technology and Arts > Department of Computing |
Identification Number: | https://doi.org/10.5121/ijaia.2016.7202 |
Page Range: | 23-35 |
Depositing User: | Helen Garner |
Date Deposited: | 22 Mar 2016 10:29 |
Last Modified: | 18 Mar 2021 06:52 |
URI: | https://shura.shu.ac.uk/id/eprint/11864 |
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