Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/406553
Title: Assessment of Health Care Insurance by Implementing Fuzzy Inference System
Researcher: Kalra, Gunjan
Guide(s): Boadh, Rahul and Rajoria, Yogendra Kumar
Keywords: Mathematics
Physical Sciences
University: K.R. Mangalam Univeristy, Gurgaon
Completed Date: 2022
Abstract: The appearance of smart living in the metro city, fine of lifestyles is certain to be improved. newlineNonetheless large want arises to offer right fitness-care offerings because the populace is more newlineand more changing into urban-centric globally. The need-gap could also be increased with the newlineassistance of contemporary technologies. Fuzzy Inference System (FIS) has used via newlineMATLAB2014b in this study with Internet of Metical Thing (IoMT) for identifying the best newlineinsurance plan for human. The worker s life is very risky and they are getting less salaries. In the newlinethesis, first risk of the human health has been identified by applying the FIS system with Blood newlinePressure, Blood sugar, Kidney functions in different age group. For the same purpose, data of the newlinehundred workers from a manufacturing industry have been considered as input in FIS. The three newlineparameters of workers such as risk of illness, salaries of the workers and age have been newlineconsidered chance for purchasing health insurance. FIS with the IoMT also used for finding the newlinebest health insurance plan for human. This thesis is advocate that, FIS may be similarly newlinesubsequently used to anticipate different kinds of health risk including intellectual and actual newlineinfection conditions, potential legitimizations to set a new approach in distinguishing planned newlinehealth care coverage buyers and may use for finding the risk factors in other industries, detect the newlinefraud case in health care industries, FIS with IoMT provide the low risk and high benefit health newlineplan to human and it may be similarly subsequently used to anticipate different kinds of health newlinerisk including intellectual and actual infection conditions. newline
Pagination: XIV 173
URI: http://hdl.handle.net/10603/406553
Appears in Departments:Department of Mathematics

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