scholarly journals Machine prediction of US imports from the PRC in the context of mutual sanctions

2020 ◽  
Vol 73 ◽  
pp. 01027
Author(s):  
Petr Šuleř ◽  
Jan Mareček
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
United States Of America ◽  
The United States ◽  
Seasonal Fluctuations ◽  
Trade Restrictions ◽  
Republic Of China ◽  
The Usa ◽  
Multilayer Perceptron Networks ◽  
Excellent Tool

The aim of this paper is to mechanically predict the import of the United States of America (USA) from the People's Republic of China (PRC). The trade restrictions of the USA and the PRC caused by the USA feeling of imbalance of trade between the two states have significantly influenced not only the trade between the two players, but also the overall climate of international trade. The result of this paper is the finding that multilayer perceptron networks (MLP) appear to be an excellent tool for predicting USA imports from the PRC. MLP networks can capture both the trend of the entire time series and its seasonal fluctuations. It also emerged that time series delays need to be applied. Acceptable results are shown to delay series of the order of 5 and 10 months. The mutual sanctions of both countries did not have a significant impact on the outcome of the machine learning prediction.

MIDDLE EAST POLICY COMPONENT OF THE USA, CHINA AND RUSSIAN FEDERATION: RUSSIAN POLICY

2021 ◽  
Vol 1 (2) ◽  
pp. 124-145
Author(s):  
D. V. GORDIENKO ◽  
Keyword(s):  
Middle East ◽  
Russian Federation ◽  
United States Of America ◽  
The United States ◽  
Republic Of China ◽  
The Usa ◽  
East Component ◽  
The Russian Federation ◽  
The Military ◽  
Middle East Policy

The paper considers the assessment of the influence of the Middle East component of the policy of the United States of America, the People's Republic of China and the Russian Federation on the national security of these countries. An approach to comparing this influence is proposed, which allows us to identify the priorities of Russia's policy in the Middle East and other regions of the world. Compare the middle East policy of the States strategic triangle Russia – China – US can be used to justify recommendations to the military-political leadership of our country.

scholarly journals Machine learning forecasting of USA and PRC balance of trade in context of mutual sanctions

2020 ◽  
Vol 73 ◽  
pp. 01025
Author(s):  
Zuzana Rowland ◽  
Jaromír Vrbka ◽  
Marek Vochozka
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Time Series ◽  
Multilayer Perceptron ◽  
Traded Goods ◽  
Suitable Tool ◽  
The Usa ◽  
Balance Of Trade ◽  
Trade War ◽  
Multilayer Perceptron Networks

The USA decided to regulate the trade more by imposing tariffs on specific types of traded goods. It is therefore more interesting to find out whether the current technologies based on artificial intelligence with time series influenced by extraordinary factors such as the trade war between two powers are able to work. The objective of the contribution is to examine and subsequently equalize two time series – the USA import from the PRC and the USA export to the PRC. The dataset shows the course of the time series at monthly intervals between January 2000 and July 2019. 10,000 multilayer perceptron networks (MLP) are generated, out of which 5 with the best characteristics are retained. It has been proved that multilayer perceptron networks are a suitable tool for forecasting the development of the time series if there are no sudden fluctuations. Mutual sanctions of both states did not affect the result of machine learning forecasting.

LATIN AMERICAN POLICY COMPONENT OF THE USA, PRC AND RUSSIAN FEDERATION POLICY OF THE PEOPLE'S REPUBLIC OF CHINA

2021 ◽  
Vol 1 (6) ◽  
pp. 150-165
Author(s):  
D. V. GORDIENKO ◽  
Keyword(s):  
Latin American ◽  
Russian Federation ◽  
United States Of America ◽  
The United States ◽  
People’S Republic Of China ◽  
People's Republic Of China ◽  
Republic Of China ◽  
The Usa ◽  
The Russian Federation ◽  
The Military

The paper considers the assessment of the influence of the Latin American component of the policy of the United States of America, the People's Republic of China and the Russian Federation on the national security of these countries. An approach is proposed to compare the influence of the Latin American component of the policy of the states of the strategic triangle Russia-China-USA, which allows us to identify the priorities of Russia's policy in Latin America and other regions of the world. The work can be used to justify recommendations to the military and political leadership of our country.

EUROPEAN POLICY COMPONENT OF THE USA, CHINA AND RUSSIAN FEDERATION (part 1)

2020 ◽  
Vol 1 (12) ◽  
pp. 90-103
Author(s):  
D. V. GORDIENKO ◽  
Keyword(s):  
United States ◽  
Russian Federation ◽  
United States Of America ◽  
The United States ◽  
Dominant Position ◽  
Republic Of China ◽  
The Usa ◽  
The Russian Federation ◽  
The Military ◽  
The Impact

The paper considers the impact of the European component of the policy of the United States of America, the people's Republic of China and the Russian Federation on the national security of these countries. An approach to comparing this influence is proposed, which allows us to identify the priorities of Russia's policy in Europe and other regions of the world. The proposed comparison can be used to justify recommendations to the military and political leadership of our country. It is concluded that the European component of the policy of the United States, China, and Russia occupies a dominant position in the implementation of current economic and military policies in the European region.

scholarly journals Considering seasonal fluctuations on balancing time series with the use of artificial neural networks when forecasting US imports from the PRC

2020 ◽  
Vol 73 ◽  
pp. 01033
Author(s):  
Jaromír Vrbka ◽  
Marek Vochozka
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Seasonal Fluctuations ◽  
Republic Of China ◽  
The World Bank ◽  
Intelligence Models ◽  
The Usa ◽  
Artificial Intelligence Models ◽  
Artificial Neural

The paper’s objective is to propose a particular methodology to be used to regard seasonal fluctuations on balancing time series while using artificial neural networks based on the example of imports from the People's Republic of China (PRC) to the USA (US). The difficulty of forecasting the volume of foreign trade is usually given by the limitations of many conventional forecasting models. For the improvement of forecasting it is necessary to propose an approach that would hybridize econometric models and artificial intelligence models. Data for an analysis to be conducted are available on the World Bank website, etc. Information on US imports from the PRC will be used. Each forecast is given by a certain degree of probability which it will be fulfilled with. Although it appeared before the experiment that there was no reason to include the categorical variable to reflect seasonal fluctuations of the USA imports from the PRC, the assumption was not correct. An additional variable, in the form of monthly value measurements, brought greater order and accuracy to the balanced time series.

scholarly journals Machine learning forecasting of CR import from PRC in context of mutual PRC and USA sanctions

2020 ◽  
Vol 73 ◽  
pp. 01017
Author(s):  
Veronika Machová ◽  
Jan Mareček
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
International Trade ◽  
Success Rate ◽  
Future Development ◽  
Trade Restrictions ◽  
Mutual Trade ◽  
The Usa

Mutual trade restrictions between the USA and the PRC caused by the USA feeling of imbalance of trade between these two countries have significantly influenced not only the trade between these two states but also the overall atmosphere of the international trade in the last few years. The objective of the contribution is to find out whether machine learning forecasting is capable of equalizing time series so that the model effectively forecasts the future development of the time series even in the context of an extraordinary situation caused by such factors as the mutual sanctions of the USA and PRC. The dataset shows the course of the time series at monthly intervals starting from January 2000 to June 2019. There is regression carried out using neural structures. Three sets of artificial neural networks are generated. They are differ in the considered time series lag. 10,000 neural networks are generated, out of which 5 with the best characteristics are retained. The mutual USA and PRC sanctions did not affect the success rate of the machine learning forecasting of the CR import from the PRC. It is evident that the mutual sanctions shall affect the trade between the CR and the PRC.

scholarly journals Forecasting trade balance of Czech Republic and People´s Republic of China in equalizing time series and considering seasonal fluctuations

2020 ◽  
Vol 73 ◽  
pp. 01032
Author(s):  
Marek Vochozka ◽  
Zuzana Rowland
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Czech Republic ◽  
Trade Balance ◽  
Seasonal Fluctuation ◽  
Seasonal Fluctuations ◽  
Republic Of China ◽  
Artificial Neural ◽  
Multilayer Perceptron Networks

The objective of the contribution is to introduce a methodology for considering seasonal fluctuations in equalizing time series using artificial neural networks on the example of the Czech Republic and the People´s Republic of China trade balance. The data available is the data on monthly balance for the period between January 2000 and July 2018, that is, 223 input data. The unit is Euro. The data for the analysis are available on the World Bank web pages etc. Regression analysis is carried out using artificial neural networks. There are two types on neural networks generated, multilayer perceptron networks (MLP) and radial basis function networks (RBF). In order to achieve the optimal result, two sets of neural structures are generated. There are generated a total of 10,000 neural structures, out of which only 5 with the best characteristics are retained. Finally, the results of both groups of retained neural networks are compared. The contribution this paper brings is the involvement of variables that are able to forecast a possible seasonal fluctuation in the time series development when using artificial neural networks. Moreover, neural networks have been identified that achieve slightly better results than other networks, specifically these are the neural networks 1. MLP 13-6-1 and 3. MLP 13-8-1.

Russian Federation and the United States of America: geostrategic directions to manage the Ukrainian crisis

2019 ◽  
pp. 123
Author(s):  
Attarid Awadh Abdulhameed
Keyword(s):  
United States ◽  
European Union ◽  
National Security ◽  
Russian Federation ◽  
United States Of America ◽  
The United States ◽  
The European Union ◽  
The Usa ◽  
Ukrainian Crisis ◽  
Zero Sum

Ukrainia Remains of huge importance to Russian Strategy because of its Strategic importance. For being a privileged Postion in new Eurasia, without its existence there would be no logical resons for eastward Expansion by European Powers.  As well as in Connection with the progress of Ukrainian is no less important for the USA (VSD, NDI, CIA, or pentagon) and the European Union with all organs, and this is announced by John Kerry. There has always ben Russian Fear and Fear of any move by NATO or USA in the area that it poses a threat to  Russians national Security and its independent role and in funence  on its forces especially the Navy Forces. There for, the Crisis manyement was not Zero sum game, there are gains and offset losses, but Russia does not accept this and want a Zero Sun game because the USA. And European exteance is a Foot hold in Regin Which Russian sees as a threat to its national security and want to monopolize control in the strategic Qirim.

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