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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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.
|Research Institute, Centre or Group:||Cultural Communication and Computing Research Institute > Communication and Computing Research Centre|
|Depositing User:||Helen Garner|
|Date Deposited:||22 Mar 2016 10:29|
|Last Modified:||21 Jan 2017 20:16|
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