<?xml version="1.0" encoding="utf-8"?>
<Journal>
<Journal-Info>
<name>International Journal of Pharma and Bio Sciences</name>
<website>ijpbs.net</website>
<email>editorijpbs@rediffmail.com (or) editorofijpbs@yahoo.com (or) prasmol@rediffmail.com</email>
</Journal-Info>
<article>
<article-id pub-id-type='other'>10.22376/ijpbs.2019.10.1.p1-12</article-id>
<issue_number>Volume 6 Issue 4</issue_number>
<issue_period>2015 (October - December)</issue_period>
<title>Fuzzy Petri Net Generated By Data Mining Rules For Diabetes Data</title>
<abstract>Fuzzy Petri nets are capable of concurrent, reliable specification of business rule engines of a core of an expert system. An expert system based on Fuzzy rule based systems are common and specification of those systems by tools like Petri nets encourage more research work nowadays. The focus of this paper is to establish an iterative scheme using data mining techniques for extractingantimal set of rules with best accuracies of such models is devised and obtained result for generating theoptimal rule base for predicting the diabetes diagnosis results.</abstract>
<authors>S.JAYASUDHA, K.RAMANATHAN AND A.KUMARAVEL</authors>
<keywords>Fuzzy logic, WEKA, Fuzzy rule base, Fuzzy Petri net, Fuzzy Inference System and Receiver Operating Characteristics (ROC), Classification, Data Mining, Selected Attributes.</keywords>
<pages>199-210</pages>
</article>
</Journal>
