DEVELOPMENT OF FUZZY INFERENCE SYSTEM FOR COVID19 DATA ANALYSIS

被引：0

作者：

Shinde-Pawar, Manisha ^{[1
]}

Patil, Jagadish ^{[1
]}

Shah, Alok ^{[2
]}

Rasal, Prasanna ^{[3
]}

机构：

[1] Bharati Vidyapeeth, Inst Management & Rural Dev Adm, Sangli, India

[2] Bharati Vidyapeeth, Dept Management Studies, Navi Mumbai, India

[3] Bharati Vidyapeeth, Yashwantrao Mohite Inst Management, Karad, India

来源：

JOURNAL OF PHARMACEUTICAL NEGATIVE RESULTS | 2022年 / 13卷 / 04期

关键词：

COVID-19; Pandemic; Fuzzy Inference System; Fuzzy Logic; Medical Stakeholders; Uncertainty;

D O I：

10.47750/pnr.2022.13.04.093

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

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.

引用

页码：693 / 699

页数：9

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