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Content Provider | IEEE Xplore Digital Library |
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Author | Rajakumar, B.R. George, A. |
Copyright Year | 2013 |
Description | Author affiliation: Aloy Labs., Bangalore, India (Rajakumar, B.R.; George, A.) |
Abstract | Heart disease is the most important reason of morbidity and mortality in the modern society. For that reason, it is important to have a proper diagnosis of heart disease for patients to live to tell the tale. In order to make the diagnosis system as the efficient one, heart diseases should be classified accurately. In the existing technique, the quality of the extracted rules is poor. So as to increase the quality of the extracted rules, an efficient technique should be used. In our proposed methodology, we are using firefly algorithm in Fuzzy Min-Max Neural Network. Firefly algorithm has high convergence tempo. It works individually and finds a superior position for itself in contemplation with its recent position as well as the situation of other fireflies. And it escapes from the local optima and finds a global optimum which has a smaller amount number of iterations. Since it is a robust algorithm, the classification of heart diseases can be done fastly and as a result the accuracy and performance of the proposed technique becomes encouraging. |
Starting Page | 1 |
Ending Page | 5 |
File Size | 155307 |
Page Count | 5 |
File Format | |
e-ISBN | 9781479939268 |
DOI | 10.1109/ICCCNT.2013.6726611 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-07-04 |
Publisher Place | India |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Heart Firefly Algorithm Fuzzy Min-Max Neural Network (FMMN) Conferences Classification algorithms Diseases Accuracy Neural networks Heart Diseases Classification Rule Mining IEEE conference proceedings Open Hyperbox |
Content Type | Text |
Resource Type | Article |
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