期刊
APPLIED AND COMPUTATIONAL MATHEMATICS
卷 20, 期 1, 页码 124-139出版社
MINISTRY COMMUNICATIONS & HIGH TECHNOLOGIES REPUBLIC AZERBAIJAN
关键词
Adaptive Neural Fuzzy Inference Systems; Fuzzy Systems; Fuzzy Logic Controller; Defuzzification
The study aims to design a system for diagnosing COVID-19 using ANFIS, and comparative analysis reveals that ANFIS model outperforms fuzzy systems in accuracy.
Artificial Intelligence has revolutionized medical sciences by providing effective ways of diagnosing various diseases. The main objective of this paper is to design a system which is able to diagnose possible presence of COVID-19 in a patient using Adaptive neuro fuzzy inference system (ANFIS). ANFIS is an approach which can be considered as a amalga-mation of artificial neural networks and fuzzy systems and hence providing advantages of both of them. Our proposed system functions with 5 variables as input and 1 variable as output. A comparative performance analysis of results obtained from ANFIS and fuzzy systems is also done which clearly depicts that ANFIS model outperforms fuzzy systems by achieving better accuracy than fuzzy systems for the diagnosis of COVID-19.
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