Earticle

초록

영어

Non Linear Cellular Automata (NLCA) as a modeling tool has received a considerable attention in recent years. Researchers from different fields have proposed various cellular automata models for addressing several problems in bioinformatics, image processing and network security .In this paper we investigate the computational properties of Non Linear Cellular Automata for building versatile and robust CA data based modeling tool for predicting heart attack.
In this paper, we investigate the non linear classes of Cellular Automata for predicting heart attack. We are mostly interested in computational properties of Non Linear Cellular Automata with decidable features and regularity. We also propose the framework of special class of non linear cellular automata named as Non Linear Multiple Attractor Cellular Automata (NLMACA). This framework is supported with genetic evolution to arrive at the desired local rules of a non linear cellular automata global function. The performances of the proposed classifier were evaluated in terms of training performances and classification accuracies and the results showed that the proposed classifier has good potential in predicting the heart attack.

목차

Abstract
 1. INTRODUCTION
 2. LITERATURE SURVEY
 3. NON LINEAR CELLULAR AUTOMATA
 4. IMPLEMENTATION ISSUES
 5. EXPERIMENTAL DETAILS
 6. CONCLUSION
 REFERENCES

저자

• P.Kiran Sree [ Principal & Head, Department of Computer Science & Engineering, NBKRIST ]
• I.Ramesh Babu [ Professor, Acharya Nagarjuna University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605