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10.1016/j.asoc.2021.107540 http://scihub22266oqcxt.onion/10.1016/j.asoc.2021.107540 34093096!8169225!34093096     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=34093096&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Appl+Soft+Comput 2021 ; 109 (ä): 107540 Nephropedia Template TP {{tp|p=34093096|t=2021. Status evaluation of provinces affected by COVID-19: A qualitative assessment using fuzzy system |pdf=|usr=}}{{34093096}} gab.com Text Status evaluation of provinces affected by COVID-19: A qualitative assessment using fuzzy system JO: Appl Soft Comput http://www.kidney.de/pget.php?&tw=1&pmid=34093096 #FOAvip The outbreak of COVID-19 had already shown its harmful impact on mankind, especially on health sectors, global economy, education systems, cultures, politics, and other important fields. Like most of the affected countries in the globe, India is now facing serious crisis due to COVID-19 in the recent times. The evaluation of the present status of the provinces affected by COVID-19 is very much essential to the government authorities to impose preventive strategies in controlling the spread of COVID-19 and to take necessary measures. In this article, a computational methodology is developed to estimate the present status of states and provinces which are affected due to COVID-19 using a fuzzy inference system. The factors such as population density, number of COVID-19 tests, confirmed cases of COVID-19, recovery rate, and mortality rate are considered as the input parameters of the proposed methodology. Considering positive and negative factors of the input parameters, the rule base is developed using triangular fuzzy numbers to capture uncertainties associated with the model. The application potentiality is validated by evaluating Pearson's correlation coefficient. A sensitivity analysis is also performed to observe the changes of final output by varying the tolerance ranges of the inputs. The results of the proposed method show that some of the provinces have very poor performance in controlling the spread of COVID-19 in India. So, the government needs to take serious attention to deal with the pandemic situation of COVID-19 in those provinces. Twit Text FOAVip Status evaluation of provinces affected by COVID-19: A qualitative assessment using fuzzy system ????Appl Soft Comput http://www.kidney.de/pget.php?&tw=1&pmid=34093096 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34093096 #FOAvip English Wikipedia <ref>{{Cite pmid|34093096}}</ref> Status evaluation of provinces affected by COVID-19: A qualitative assessment using fuzzy system #MMPMID34093096 Ghosh B; Biswas A Appl Soft Comput 2021[Sep]; 109 (ä): 107540 PMID34093096show ga The outbreak of COVID-19 had already shown its harmful impact on mankind, especially on health sectors, global economy, education systems, cultures, politics, and other important fields. Like most of the affected countries in the globe, India is now facing serious crisis due to COVID-19 in the recent times. The evaluation of the present status of the provinces affected by COVID-19 is very much essential to the government authorities to impose preventive strategies in controlling the spread of COVID-19 and to take necessary measures. In this article, a computational methodology is developed to estimate the present status of states and provinces which are affected due to COVID-19 using a fuzzy inference system. The factors such as population density, number of COVID-19 tests, confirmed cases of COVID-19, recovery rate, and mortality rate are considered as the input parameters of the proposed methodology. Considering positive and negative factors of the input parameters, the rule base is developed using triangular fuzzy numbers to capture uncertainties associated with the model. The application potentiality is validated by evaluating Pearson's correlation coefficient. A sensitivity analysis is also performed to observe the changes of final output by varying the tolerance ranges of the inputs. The results of the proposed method show that some of the provinces have very poor performance in controlling the spread of COVID-19 in India. So, the government needs to take serious attention to deal with the pandemic situation of COVID-19 in those provinces. äStatus evaluation of provinces affected by COVID-19: A qualitative ass(epmc).pdf DeepDyve Pubget Overpricing