DEVELOPMENT OF FUZZY INFERENCE SYSTEM FOR COVID-19 DATA ANALYSIS

Author:

Manisha Shinde-Pawar ,Jagadish Patil ,Alok Shah ,Prasanna Rasal

Abstract

As COVID-19 Pandemic and related data is very recent. COVID-19 infected most of the population from entire globe with different impact. It disclosed the limitation of access of health and care resources. Various parameters like different symptoms, different existing health conditions, different age, diagnosis level and great uncertainties made the condition vaguer. Fuzzy can handle such vagueness and uncertainty of such voluminous data of patients and can support to medical stakeholders, experts, hospitals, pharmaceuticals etc. Fuzzy Logic is widely used to address so many uncertainties, incompleteness or imprecision. The current experiment implements Fuzzy Inference System for pattern identification and classification by applying fuzzy approach with Fuzzy Logic in R for performance improvement. This focuses on designing Fuzzy Rule base, Model and inference for COVID 19 data analysis.

Publisher

Siree Journals

Subject

Drug Discovery,Pharmaceutical Science,Pharmacology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Uncertainty Resolution with Fuzzy Inference System Approach towards Stress, Anxiety, and Depression;International Journal of Computational and Applied Mathematics & Computer Science;2022-12-31

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