Abstract

In this study we propose a model of an Expert Syste m to diagnose a car failure and malfunction using Bayesian Approach. An expert car failure diagnosis system is a computer system that uses specific knowledge which is owned by an expert to resolve car problems. Our specific system consists of knowled ge base and solution to diagnose failure of car from T oyota Avanza, one of the favorite car used in Indon esia today and applying Bayesian approach for knowing the belief of the solution. We build Knowledge representation techniques of symptoms and solution froman experts using production rules. The experimental results presented and we obtained that the system has been able to perform diagnosis on c ar failure, giving solution and also gives the probabi lity value of that solution.

Highlights

  • The Expert System (ES) is a computer system that emulates the decision-making ability of a human expert in a restricted domain

  • In this study we propose a model of an Expert System to diagnose a car failure and malfunction using Bayesian Approach

  • An expert car failure diagnosis system is a computer system that uses specific knowledge which is owned by an expert to resolve car problems

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Summary

INTRODUCTION

The Expert System (ES) is a computer system that emulates the decision-making ability of a human expert in a restricted domain. In ES, human knowledge about a particular expertise to accomplish a particular task is represented as facts and rules in its knowledge base (Salama et al, 2012). It seeks and uses the information provided by a user. With the possibility of true values of the probability calculations Bayesian user will more take a decision on damages For these reasons, it is done research entitled “Analysis and Design of Expert System for Diagnosing Damage On Four Wheels Vehicles with Bayesian Probability Approach” to the maximum in order to give a more precise diagnostic possibilities because it can diagnose the onset of damage to the car so that the damage does not getting worse.

Car Diagnosis Principles
The Knowledge Base
The Inference Engine
Experimental Results
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