A mathematical conflict resolution methodology using logic scoring of preference sampled in a theoretical medical data

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Article

Source Title

Global Journal of Pure and Applied Mathematics

Volume

12

Issue

4

First Page

3133

Last Page

3142

Publication Date

1-1-2016

Abstract

In certain areas like Network Based Control Systems, Communication Systems and Medical Diagnosis there are problems that are encountered. The problems that are encountered are either recurrent or new ones. Recurrent problems have well defined structured solutions and they also represent majority of the problems. The new ones do not yet have solutions and requires investigations to discover their roots. New problems are not the primary concern in most systems since they rarely occur. The major concerns are the recurrent problems; they are often mistaken as new ones. The solutions to new problems are rediscovered after much trial and error in which time is wasted costing the company valuable resources. An Expert System can be used for problems that keep on occurring. This system can reproduce a valuable technician’s. The system can give an accurate recommendation on the source of the problem for effective troubleshooting before going to the mobilization of resources. One predicament in Expert Systems is that their knowledge base may contain numerous data and suggest different types of solutions to a certain problem. The Expert System may have narrowed out the cause of the problem but it still must give a weight to the ones it has suggested to what the most probable cause. This paper proposes a Conflict Resolution methodology using Logic Scoring of Preference which can be used in several applications like Expert Systems. A sample application is also shown in the medical field. This will greatly help for the user to sequence its diagnostic procedures and solve a problem efficiently. © Research India Publications.

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Disciplines

Electrical and Computer Engineering

Keywords

Expert systems (Computer science); Decision support systems; Artificial intelligence—Medical applications

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