Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/192566
Title: Analysis of Risk Factors of Hert Disease Using Decagonal Fuzzy Models
Researcher: Divya A
Guide(s): Dr. P.S. Sehik Uduman
Keywords: Risk factors, Heart Disease, Decagonal, Fuzzy Models
University: B S Abdur Rahman University
Completed Date: 
Abstract: The contribution of this thesis is based on analyzing the risk factors of heart disease. Heart disease is one of the foremost reasons for death throughout the world. It leads to high mortality in both men and women. Risk factors play a vital role in developing heart disease. newlineThis thesis involves developing a model based on decagonal fuzzy number (DFN) for analyzing the risk factors for heart disease. Risk factors vary from person to person for finding the vagueness. Here, three models are developed such as fuzzy risk analysis based on the Decagonal fuzzy number (DFN), the Modified Decagonal fuzzy cognitive map (MDFCM) and fuzzy arbitrary order predator-prey model using DFN. These models are applied to analyze the risk factors of heart disease using primary data from the Cuddalore district in Tamilnadu. newlineFuzzy risk analysis model is used for finding the probability of failure and severity of loss of the cardiovascular system and has been analyzed using an interval-valued decagonal approximation of the fuzzy number. For ranking the major risk factors of heart disease for men, women and pregnancy women the MDFCM is developed and is divided into two categories namely the Expert s opinion model and data collection method. The six new models of fuzzy arbitrary order predator-prey models are developed using a homotopy perturbation technique through Triangular fuzzy number and DFN. It has been developed for predicting the time when the predator-prey meets each other. Here the predators are the risk factors for heart disease and the prey refers to the patients with heart problems and also predicting the time of pregnancy induced hypertension (PIH) for women. newlineIn this thesis Induced fuzzy cognitive map (IFCM) is used for finding the major reasons of obesity. Fuzzy rule (FR) based system is used for finding the threshold value of fast food eaters using Mamdhani rule in MATLAB. The study has been carried out at heart care clinic situated in Thirupapuliyur, Cuddalore district of Tamilnadu. The primary data has been
Pagination: 189
URI: http://hdl.handle.net/10603/192566
Appears in Departments:Department of Mathematics

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