A system used for collecting and managing graphic elements of Yunnan heavy color painting

Pu, Yuanyuan; Su, Yi; Wei, Xiaomin; Qian, Wei; Zhao, Zhengpeng; Xu, Dan

doi:10.1109/iasp.2010.5476140

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…It influences the number of liabilities and current installments of long-haul unfamiliar cash credits quantifiably (in Poland, particularly those named in CHF). It is sensible to expect that a fortifying of the conversion scale would weaken the installment capacity of lenders who do not have unfamiliar cash inflows, bringing about another round of lawful activity against machine learnings [37]. This sort of borrowers' lawful exercises in Poland expanded well before the pandemic, because of the court decisions for debt holders by the court of justice of the (CJEU).…”

Section: Covid-19 Pandemic and Its Machine Learning Area Within Santa...mentioning

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: Covid-19 Pandemic and Its Machine Learning Area Within Santa...mentioning

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

A system used for collecting and managing graphic elements of Yunnan heavy color painting

Cited by 1 publication

References 9 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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