scholarly journals Early Identification of COVID-19 Using Dynamic Fuzzy Rule Based System

2021 ◽  
Vol 8 (5) ◽  
pp. 805-812
Author(s):  
Mohammed Imran Basheer Ahmed ◽  
Atta-ur Rahman ◽  
Mehwash Farooqui ◽  
Fatimah Alamoudi ◽  
Raghad Baageel ◽  
...  
Keyword(s):  
Healthcare Professionals ◽  
Fuzzy Rule ◽  
Fuzzy Membership Function ◽  
Membership Functions ◽  
Dynamic Nature ◽  
Rule Based ◽  
Infected People ◽  
Rule Based System ◽  
Global Pandemic ◽  
The Common

The undergoing research aims to address the problem of COVID-19 which has turned out to be a global pandemic. Despite developing some successful vaccines, the pace has not overcome so far. Several studies have been proposed in the literature in this regard, the present study is unique in terms of its dynamic nature to adapt the rules by reconfigurable fuzzy membership function. Based on patient’s symptoms (fever, dry cough etc.) and history related to travelling, diseases/medications and interactions with confirmed patients, the proposed dynamic fuzzy rule-based system (FRBS) identifies the presence/absence of the disease. This can greatly help the healthcare professionals as well as laymen in terms of disease identification. The main motivation of this paper is to reduce the pressure on the health services due to frequent test assessment requests, in which patients can do the test anytime without the need to make reservations. The main findings are that there is a relationship between the disease and the symptoms in which some symptoms can indicate the probability of the presence of the disease such as high difficulty of breathing, cough, sore throat, and so many more. By knowing the common symptoms, we developed membership functions for these symptoms, and a model generated to distinguish between infected and non-infected people with the help of survey data collected. The model gave an accuracy of 88.78%, precision of 72.22%, sensitivity of 68.42%, specificity of 93.67%, and an f1-score of 69.28%.

A fuzzy rule-based system to assess e-government technical interoperability maturity level

2014 ◽  
Vol 8 (3) ◽  
pp. 335-356 ◽  
Author(s):  
Andreiwid Sheffer Corrêa ◽  
Alexandre de Assis Mota ◽  
Lia Toledo Moreira Mota ◽  
Pedro Luiz Pizzigatti Corrêa
Keyword(s):  
Fuzzy Rule ◽  
Assessment Process ◽  
Maturity Model ◽  
Maturity Level ◽  
Rule Based ◽  
Content Type ◽  
Management Level ◽  
Rule Based System ◽  
Brazilian Government ◽  
Information And Communication

Purpose – The purpose of this study is to present a system called NEBULOSUS, which is a fuzzy rule-based expert system for assessing the maturity level of an agency regarding technical interoperability. Design/methodology/approach – The study introduces the use of artificial intelligence and fuzzy logic to deal with the imprecision and uncertainty present in the assessment process. To validate the system proposed and demonstrate its operation, the study takes into account the Brazilian technical interoperability maturity model, based on the Brazilian Government Interoperability Framework (GIF). Findings – With the system proposed and its methodology, it could be possible to increase the assessment process to management level and to provide decision-making support without worrying about technical details that make it complex and time-consuming. Moreover, NEBULOSUS is a standalone system that offers an easy-to-use, open and flexible structuring database that can be adapted by governments throughout the world. It will serve as a tool and contribute to governments’ expectations for continuous improvement of their technologies. Originality/value – This study contributes toward filling a gap in general interoperability architectures, which is a means to provide an objective method to evaluate GIF adherence by governments. The proposed system allows governments to configure their technical models and GIF to assess information and communication technology resources.

Assessing flood vulnerability using a rule-based fuzzy system

2012 ◽  
Vol 66 (8) ◽  
pp. 1766-1773 ◽  
Author(s):  
J. Yazdi ◽  
S. A. A. S. Neyshabouri
Keyword(s):  
Fuzzy Rule ◽  
Vulnerability Analysis ◽  
Human Knowledge ◽  
Small Watershed ◽  
Flood Vulnerability ◽  
Rule Based ◽  
Rule Based System ◽  
Vulnerability Map ◽  
Flood Prone Areas

Population growth and urbanization in the last decades have increased the vulnerability of properties and societies in flood-prone areas. Vulnerability analysis is one of the main factors used to determine the necessary measures of flood risk reduction in floodplains. At present, the vulnerability of natural disasters is analyzed by defining the various physical and social indices. This study presents a model based on a fuzzy rule-based system to address various ambiguities and uncertainties from natural variability, and human knowledge and preferences in vulnerability analysis. The proposed method is applied for a small watershed as a case study and the obtained results are compared with one of the index approaches. Both approaches present the same ranking for the sub-basin's vulnerability in the watershed. Finally, using the scores of vulnerability in different sub-basins, a vulnerability map of the watershed is presented.

Corner Detection Using Fuzzy Principles

2013 ◽  
pp. 498-512
Author(s):  
Erik Cuevas ◽  
Daniel Zaldivar ◽  
Marco Perez-Cisneros
Keyword(s):  
Pattern Recognition ◽  
Fuzzy Systems ◽  
Fuzzy Rule ◽  
Important Task ◽  
Fuzzy Rules ◽  
Corner Detection ◽  
Illumination Change ◽  
Benchmark Test ◽  
Rule Based ◽  
Rule Based System

Reliable corner detection is an important task in pattern recognition applications. In this chapter an approach based on fuzzy-rules to detect corners even under imprecise information is presented. The uncertainties arising due to various types of imaging defects such as blurring, illumination change, noise, et cetera. Fuzzy systems are well known for efficient handling of impreciseness. In order to handle the incompleteness arising due to imperfection of data, it is reasonable to model corner properties by a fuzzy rule-based system. The robustness of the proposed algorithm is compared with well known conventional detectors. The performance is tested on a number of benchmark test images to illustrate the efficiency of the algorithm in noise presence.

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