Development of Excessive-Smoke-Emitting-Car Fault Diagnostic System (ESECFDS) based on Case-Base Reasoning (CBR) Methodology-Reference-Cited by-同舟云学术

Development of Excessive-Smoke-Emitting-Car Fault Diagnostic System (ESECFDS) based on Case-Base Reasoning (CBR) Methodology

Published:2021-04-09 Issue:1 Volume:25 Page:75-95
ISSN:1327-2314
Container-title:International Journal of Knowledge-based and Intelligent Engineering Systems
language:
Short-container-title:KES

Author:

De Sumana,Chakraborty Baisakhi

Abstract

This paper proposes a diagnostic system, ESECFDS, to solve the problem of excessive smoke emission from a faulty car, based on Case-Based Reasoning (CBR) Methodology that accepts a user query as a new case, compares it with several stored cases in a Case-Base (CB) based on a similarity score using Jaccard Similarity method and provides feedback result to the user. The CBR cycle R4 Model of Aamodt and Plaza has been modified to R5 Model to improve the time complexity of the proposed algorithm of the system over the popular R4 Model.

Publisher

IOS Press

Subject

Artificial Intelligence,Control and Systems Engineering,Software

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