A system of serial computation for classified rules prediction in non-regular ontology trees

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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Official URL: http://www.airccse.org/journal/ijaia/current2016.h...
Link to published version:: 10.5121/ijaia.2016.7202

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
Research Institute, Centre or Group: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Identification Number: 10.5121/ijaia.2016.7202
Depositing User: Helen Garner
Date Deposited: 22 Mar 2016 10:29
Last Modified: 07 Dec 2016 19:16
URI: http://shura.shu.ac.uk/id/eprint/11864

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