Assessment of the Contribution of Some Observable Factors to the Dynamics of Poverty in the Russian Federation Using the Apparatus of Neural Networks-Reference-Cited by-同舟云学术

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Assessment of the Contribution of Some Observable Factors to the Dynamics of Poverty in the Russian Federation Using the Apparatus of Neural Networks

Published:2022-11-09 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA)
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Author:

Karlova Margarita¹,Kozlova Elena²,Ryazantseva Elena³

Affiliation:

1. Institute of Natural, Mathematical and Technical Sciences Lipetsk State Pedagogical University named after P.P. Semenov-Tyan-Shanskiy,Lipetsk,Russia

2. Institute of Social Sciences, Economics and Law Lipetsk State Technical University,Lipetsk,Russia

3. Financial University under the Government of the Russian Federation (Lipetsk Branch),Department “Accounting and Information Technologies in Business”,Lipetsk,Russia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9973814/9973434/09974072.pdf?arnumber=9974072

Reference19 articles.

1. Resilient Backpropagation Neural Network on Prediction of Poverty Levels in South Sulawesi

2. Modeling the poverty level in the Russian Federation based on a neural network approach;karlova;Aktual'nye napravlenija nauchnyh issledovanij XXI veka teorija i praktika,2021

3. Poverty in Russian regions in 2000-2017: factors and dynamics

4. Poverty in Russia: the main factors;shangin;Novainfo,2017

5. THE FACTORS, WHICH ARE INFLUENCING ON THE POVERTY LEVEL IN THE REGION: THE REGRESSION ANALYSIS (ON THE EXAMPLE OF THE ULYANOVSK REGION)

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