Design and Realization of NC Graphic Programming System

Wang, Pin; Su, Lan-zhi

doi:10.1109/wcse.2010.54

Cited by 1 publication

(1 citation statement)

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“…The basel committee on machine learning supervision (BCBM) was coordinated because of worries about the impact of government drives helping the corporate area on machine learning announcing. BCBM conveyed a lot of ideas as answers to pre-picked requests in April 2020 [28]. The paper looks at how to understand authorization related to surveying potential damages and seeing redesigns in the data mining and data mining condition of machine learning obligation holders in reports [29].…”

Section:  Issn: 2252-8776mentioning

confidence: 99%

Evaluating the impact of COVID-19 on the monetary crisis by machine learning

Mohseni

2023

IJ-ICT

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In this study, machine learning is examined in relation to commercial machine learning's resilience to the COVID-19 pandemic-related crisis. Two approaches are used to assess the pandemic's impact on machine learning risk, as well as a method to prioritize sectors according to the crisis's potential negative consequences. I conducted the study to determine Santander machine learning's resilience. The data mining area offers prospects for COVID-19's future. A total of 13 machine learning demos were selected for its organization. The Hellweg strategy and the technique for order preference by similarity to ideal solution (TOPSIS) technique were utilized as direct request strategies. Parametric assessment of machine learning versatility in business was based on capital sufficiency, liquidity proportion, market benefits, and share in an arrangement of openings with a perceived disability, and affectability of machine learning's credit portfolio to monetary hazard. As a result of the COVID-19 pandemic, these enterprises were ranked according to their threat. Based on the findings of the research, machine learning worked the best for the pandemic. Meanwhile, machine learning suffered the most during the downturn. It can be seen, for example, in conversations about the impact of the pandemic on developing business sector soundness and managing financial framework solidity risk.

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Section:  Issn: 2252-8776mentioning

confidence: 99%

Evaluating the impact of COVID-19 on the monetary crisis by machine learning

Mohseni

2023

IJ-ICT

View full text Add to dashboard Cite

show abstract

Design and Realization of NC Graphic Programming System

Cited by 1 publication

References 3 publications

Evaluating the impact of COVID-19 on the monetary crisis by machine learning

Evaluating the impact of COVID-19 on the monetary crisis by machine learning

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