scholarly journals Comparison of neural networks and regression time series in predicting export from Czech Republic into People´s Republic of China

2020 ◽  
Vol 73 ◽  
pp. 01015
Author(s):  
Tomáš Krulický ◽  
Tomáš Brabenec
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Czech Republic ◽  
Statistical Methods ◽  
Chinese Market ◽  
Republic Of China ◽  
The People ◽  
Short Period ◽  
The World ◽  
Year 2000

The People´s Republic of China is one of the largest, but also the most demanding markets in the world. The trade is limited by a number of barriers, strong competition and unusual environment for trades from other parts of the world. Despite those limitations, Czech exporters are able to establish themselves in the Chinese market, exporting mainly machines and vehicles. To predict future export trends is very difficult; however, these predictions can be crucial not only for individual exporters but also for the whole national economy. For predictions, economists use causal, intuitive or statistical methods. The objective of the contribution is to compare the accuracy of equalizing time series by means of regression analysis and artificial neural networks for a possible prediction of future export trends on the example of the Czech Republic export to the People´s Republic of China. For the purposes of analysis by means of statistical methods, the data obtained from monthly statements from the period starting from the year 2000 and ending in July 2018. First, a linear regression is carried out and subsequently, neural networks are used for regression. Finally, the results are compared. It appeared that in practice, mainly all retained neural networks are applicable. However, the first of them showed significant deviations within a very short period of time.

scholarly journals Using Artificial Neural Networks for Equalizing Time Series Considering Seasonal Fluctuations

2019 ◽  
Vol 71 ◽  
pp. 01003
Author(s):  
J. Vrbka ◽  
J. Horák ◽  
V. Machová
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Seasonal Fluctuations ◽  
Republic Of China ◽  
The People ◽  
Data Points ◽  
Artificial Neural ◽  
The Individual

The objective of this contribution is to prepare a methodology of using artificial neural networks for equalizing time series when considering seasonal fluctuations on the example of the Czech Republic import from the People´s Republic of China. If we focus on the relation of neural networks and time series, it is possible to state that both the purpose of time series themselves and the nature of all the data are what matters. The purpose of neural networks is to record the process of time series and to forecast individual data points in the best possible way. From the discussion part it follows that adding other variables significantly improves the quality of the equalized time series. Not only the performance of the networks is very high, but the individual MLP networks are also able to capture the seasonal fluctuations in the development of the monitored variable, which is the CR import from the PRC.

scholarly journals Machine learning forecasting of CR and PRC balance of trade

2020 ◽  
Vol 73 ◽  
pp. 01004
Author(s):  
Tomàš Brabenec ◽  
Petr Šuleř
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Time Series ◽  
Data Set ◽  
Republic Of China ◽  
The People ◽  
The Future ◽  
Balance Of Trade ◽  
Political Economic ◽  
Social Importance

International trade is an important factor of economic growth. While foreign trade has existed throughout the history, its political, economic and social importance has grown significantly in the last centuries. The objective of the contribution is to use machine learning forecasting for predicting the balance of trade of the Czech Republic (CR) and the People´s Republic of China (PRC) through analysing and machine learning forecasting of the CR import from the PRC and the CR export to the PRC. The data set includes monthly trade balance intervals from January 2000 to June 2019. The contribution investigates and subsequently smooths two time series: the CR import from the PRC; the CR export to the PRC. The balance of trade of both countries in the entire monitored period is negative from the perspective of the CR. A total of 10,000 neural networks are generated. 5 neural structures with the best characteristics are retained. Neural networks are able to capture both the trend of the entire time series and its seasonal fluctuations, but it is necessary to work with time series lag. The CR import from the PRC is growing and it is expected to grow in the future. The CR export to the PRC is growing and it is expected to grow in the future, but its increase in absolute values will be slower than the increase of the CR import from 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.

scholarly journals Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance

2019 ◽  
Vol 61 ◽  
pp. 01023 ◽  
Author(s):  
Zuzana Rowland ◽  
Petr Šuleř ◽  
Marek Vochozka
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Czech Republic ◽  
Linear Regression ◽  
Trade Balance ◽  
People’S Republic Of China ◽  
People's Republic Of China ◽  
The Czech Republic ◽  
Republic Of China ◽  
China Trade

Foreign trade has been and is considered to be very important. Trade balance measurement provides one of the best analyzes of a country's external economic relations. It serves as a monetary expression of economic transactions between a certain country and its foreign partners over a certain period. The aim of this paper is to compare the accuracy of time series alignment by means of regression analysis and neural networks on the example of the trade balance of the Czech Republic and the People's Republic of China. Trade balance data between the Czech Republic and the People's Republic of China is used. This is a monthly balance starting in 2000 and ending in July 2018. First, a linear regression is made followed by regression using artificial neural networks. A comparison of both methods at expert level and experience of the evaluator, the economist, is performed. Optically, the LOWESS curve appears to be best out of the linear regression and the fifth preserved RBF 1-24-1 network seems the mot appropriate out of neural networks.

Influence of Renminbi Internationalization on China’s Monetary Policy Effects: A Theoretical Analysis

2021 ◽  
Vol 13 (8) ◽  
pp. 14
Author(s):  
Huiguan Ding ◽  
Asli Ogunc ◽  
Dale Funderburk ◽  
Shiyou Li ◽  
Zhebie Shi
Keyword(s):  
Monetary Policy ◽  
Open Economy ◽  
Analytical Framework ◽  
Securities Markets ◽  
Republic Of China ◽  
Policy Effects ◽  
The People ◽  
The World ◽  
The Impact ◽  
Rmb Internationalization

For more than a decade, the People’s Republic of China has sought to expand the degree of internationalization of its official currency. In recent decades, China has become the world’s second largest economy, as well as the world’s largest trading nation, and its securities markets are among the largest in the world. Today, the RMB is among the top five as a world payments currency. One of the significant costs of achieving higher degrees of internationalization of a country’s currency is the complicating impact it has on the efficacy and effect of that country’s domestic monetary policy.  However, what is the nature and extent of that complicating impact? This paper employs an IS-LM model of an open economy as an analytical framework, embeds an RMB internationalization factor into that model. Specifically, with this model we examine the impact of RMB internationalization on the effects of China’s monetary policy. 

A Study of Translation Methods Adopted in the Yangs’ Version of “Master Gao” from the Perspective of Manipulation Theory

2021 ◽  
Vol 11 (4) ◽  
pp. 32
Author(s):  
Ruijing Qin ◽  
Chengfa Yu
Keyword(s):  
Short Stories ◽  
Short Story ◽  
Chinese Culture ◽  
Social Background ◽  
Lu Xun ◽  
Domestic Environment ◽  
Republic Of China ◽  
The People ◽  
The World ◽  
Translation Methods

Soon after the founding of the People’s Republic of China in 1949, foreign translation of Chinese culture was put on the agenda. Lu Xun’s short stories were selected as representative works and translated into English by Yang Xianyi and Gladys Yang (hereinafter referred to as “the Yangs”) in the 1950s and 1960s under the special international and domestic environment, and they have played an important role in spreading Chinese culture to the world. Based on André Lefevere’s Manipulation Theory, especially its three elements, namely, poetics, ideology and patronage, this paper examines the translation methods adopted by the Yangs in their translation of Lu Xun’s short story “Master Gao”. Through example analysis, the article concludes that the Yangs mainly adopted literal translation under the influence of poetics, ideology and patronage in the then special social background. It is hoped that the research aims to provide a theoretical and practical reference for future translation and dissemination of Chinese literary works to the world.

FAULT-FREE ECONOMICS: PROPHETIC PERSPECTIVES

2020 ◽  
Vol 19 ◽  
Author(s):  
Abdul Rashid
Keyword(s):  
Primary Objective ◽  
Future Generations ◽  
Human Society ◽  
The People ◽  
Short Period ◽  
The Reformation ◽  
The World ◽  
Right Reason ◽  
The Right ◽  
Holy Man

Allah commanded the Prophet Muhammad (ﷺ) to inform the people in the following way: O' my people, do you see whether I am on the (right) reason from my Lord Who provided me with the best subsistence, and I only intend to reform as far as possible, and whatever my capacities are, they are from Allah upon whom I have trust and revert to Him (for guidance and help.) In this verse, the Qur'an has given the words that Hazrat Shoaib (A.S) used for the reformation of his nation. This also makes obvious the fact that the primary objective of the advent of Messengers has been the reformation of society. This great reformatory work was performed from Hazrat Adam (A.S.) up till Hazrat Isa according to the prevalent situation of their times. But after these holy personalities, their followers tampered with their teachings. Subsequently a personality was sent (by Allah) who in the light of the divine teachings pledged to reform not only his own people but the whole world. This holy man was Hazrat Muhammad (ﷺ) who came to this world fourteen hundred and sixty years ago as Mercy for All the Worlds By virtue of his magnanimity, he turned the darkness of the world into light. He reformed the society, uprooting all the evils of the human society, in such a manner that this society, corrupt for centuries, instantly turned into one that became exemplary for future generations. In other words, he, Muhammad (p.b.u.h) reformed the worst society of the world successfully, effectively and in a very short period of time.

scholarly journals Current measures to maintain the stability of workers in Slovak companies

2020 ◽  
Vol 83 ◽  
pp. 01030
Author(s):  
Jana Kissová ◽  
Gabriela Dubcová
Keyword(s):  
Czech Republic ◽  
Slovak Republic ◽  
Emergency Situation ◽  
Current Situation ◽  
Economic Dimension ◽  
The Czech Republic ◽  
The Social ◽  
Short Period ◽  
The World ◽  
The Stability

Over a short period of time, individual countries in the world face a common problem that affects them and adversely affects the lives of individuals. In connection with the current emergency situation related to the corona virus pandemic, it is possible to notice fundamental changes and enormous impact in the social or economic dimension. The aim of the article is to provide an overview of the current situation in selected countries and to compare the system of measures in the Slovak Republic and the Czech Republic that were adopted in order to stabilize or retain workers or aimed at elimination of imminent damage.

scholarly journals The world's view of the Corona pandemic and the way to deal with it: نظرة العالم إلى جائحة كورونا وأسلوب التّعامل معها

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Amara Saad Chandoul, Widad Ali Zughir
Keyword(s):  
Political System ◽  
World Health ◽  
The Third ◽  
The Poor ◽  
The People ◽  
Short Period ◽  
The World ◽  
Descriptive Approach ◽  
Health Organization ◽  
Insight Into

In this paper, the researcher stresses that the crisis of Corona, which the world has gone through and is still primarily a crisis of awareness in providing priorities. This predicts the emergence of serious economic and social problems that may afflict existing societies and systems, or arrange them in a worse way, as the foundations of justice in the world are broken. The researcher notes that the world around the pandemic is divided into three parts : The first part, whoever claims to be a true pandemic is a caution, and they are in two directions : The first one is for whoever thinks that the pandemic is natural and requires cooperation in finding a solution and complying with the provisions of the World Health Organization. The second concern whoever goes on to say that the pandemic is an effective act, and he has all the information about it and has to disclose and stop spreading it to protect humanity. The second part cover people who deny the seriousness of the pandemic and that it is just a conspiracy in preparation for the adoption of a new political system that rules the world, increases the servitude of the people and oppresses the poor, and they are in two directions: The first one, concern people who deny the existence of such a virus in the first place. The second, includes who acknowledges his existence and excludes his danger. The third part, is the part of persons holding that the existence of a pandemic or does not matter as much as it matters how to deal with it and with similar counterparts that are not literally dangerous to it, and the originality of their duty is to seek the assistance of the qualified and specialized, to provide the most important on the important and to present alternatives that prove sustainability as possible and possible. This is because the boasting of building hospitals in a short period was not accompanied by building laboratories to eradicate such a scourge and others that we live in and may be experienced by humanity in the future. The research concluded that it is necessary to not look into the existence or absence of the pandemic, but rather to look at how to deal with it and overcome it and its counterparts, without stopping people's lives or political exploitation of the crisis. It deals also to be careful in order that fear does not dominate us at the point of illusion, and to look with insight into what can carry conspiracy. The researcher adopted the inductive approach, by tracking people's opinions about COVID-19. The research also dealt with the descriptive approach, in presenting these opinions, in analyzing and clarifying their evidence, clarifying what is in, and discussing it.

scholarly journals How to Predict the Spread of COVID-19

2021 ◽  
Author(s):  
Eduard Dadyan
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Predictive Model ◽  
Discrete Time ◽  
Russian Federation ◽  
Time Frame ◽  
The World ◽  
The Russian Federation ◽  
Equidistant Points

Abstract For analysis tasks, time counts are of interest – values recorded at some, usually equidistant, points in time. The calculation can be performed at various intervals: after a minute, an hour, a day, a week, a month, or a year, depending on how much detail the process should be analyzed. In time series analysis problems, we deal with discrete-time, when each observation of a parameter forms a time frame. The same can be said about the behavior of Covid-19 over time.In this paper, we solve the problem of predicting Covid-19 diseases in the world using neural networks. This approach is useful when it is necessary to overcome difficulties related to non-stationarity, incompleteness, unknown distribution of data, or when statistical methods are not completely satisfactory. The problem of forecasting is solved with the help of the analytical platform Deductor Studio, developed by specialists of the company Intersoft Lab of the Russian Federation. When solving this problem, appropriate methods were used to clean the data from noise and anomalies, which ensured the quality of building a predictive model and obtaining forecast values for tens of days ahead. The principle of time series forecasting was also demonstrated: import, seasonal detection, cleaning, smoothing, building a predictive model, and predicting Covid-19 diseases in the world using neural technologies for 30 days ahead.

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