scholarly journals Mathematical modeling and forecasting of seasonal characteristics of tourist flow

2021 ◽  
Vol 264 ◽  
pp. 01042
Author(s):  
Sherkul Rakhmanov ◽  
Ibrohim Habibullaev ◽  
Akbar Jumaev ◽  
Tolib Turgunov
Keyword(s):  
Time Series ◽  
Additive Model ◽  
Econometric Modeling ◽  
Methods Of Analysis ◽  
Seasonal Characteristics ◽  
Tourism Sector ◽  
Tourist Flows ◽  
Modeling And Forecasting ◽  
The Republic ◽  
Tourist Flow

The article describes the flow of tourists to the Republic of Uzbekistan and the methods of analysis and forecasting based on econometric modeling of the development of the process based on its seasonal characteristics. Econometric modeling methods developed by foreign and local scientists were analyzed and divided into groups to analyze the process of changing the flow of tourists and predict the future number. Among them, the additive model in the group of time series reflecting the seasonality of tourist flow was found to meet the conditions. Based on the data obtained in the quarters for 2014-2018, the values of the trend (T), seasonal (S), and random (E) components of the time series were calculated step by step, and an additive model of the process was developed. Based on the developed model, the forecast values of tourist flow for the next quarter were determined, and the deviation from the actual value of the theoretical result was 20%, and the occurrence of this deviation was clarified. Forecasts of changes in the statistics of the tourism sector have been developed. The article describes the methods of analysis and forecasting of tourist flows and seasonality of the Republic of Uzbekistan based on econometric modeling.

scholarly journals Geography of Tourist Flows in the Republic of Mordovia

REGIONOLOGY ◽  
2021 ◽  
Vol 29 (4) ◽  
pp. 866-885
Author(s):  
Marina A. Zhulina ◽  
Vyacheslav M. Kitsis
Keyword(s):  
Tourism Industry ◽  
Managerial Decisions ◽  
Tourism Management ◽  
Tourism Sector ◽  
Tourist Flows ◽  
Effective Program ◽  
The Republic ◽  
Tourism Service ◽  
Effective Development ◽  
Tourist Flow

Introduction. The topic is of relevance due to the need to study tourist flows in terms of the geography of tourist trips in order to analyze and compare the directions of the flows. The problem is that the authorities responsible for tourism management in the region and tourism organizations do not always pay due attention to the geography of the tourist flow and to its optimization in terms of the interests of the region itself. At the same time, the identified trends can be taken into consideration in order to improve and increase the efficiency of the tourism industry in the region and when making managerial decisions in the tourism sector. Based on the results of the study conducted, the article characterizes the travel destinations of Mordovian tourists, reveals trends, and proposes measures to solve the identified problems. Materials and Methods. The materials on the development of tourism in the Republic of Mordovia published by the Territorial Body of the State Statistics Service in the Republic of Mordovia for the period from 2010 to 2019 were analyzed; data from the Digital Tourism service run by MegaFon mobile phone operator were also examined. The methods of mathematical statistics employed made it possible to calculate the changes in the relative and absolute indicators of the geography of the tourist flow in the republic over a ten-year period. To identify the geography of the regional tourist flow, the methods of analysis and generalization were used, which made it possible to identify the features of the internal and external tourist flows of people living in Mordovia. Results. An analysis of the dynamics and placement of inbound and outbound tourism has been carried out; the volume of the tourist flow has been considered; the features of the geography of the tourist flows have been considered; the problems that hinder the more effective development of tourism in the republic have been revealed. The measures aimed at improving the efficiency of tourism activities in the region have been proposed. Discussion and Conclusion. The study made it possible to identify the main trends in the geography of the tourist flows of residents of Mordovia, as well as the causes and features of the ongoing transformations. The results of the study can contribute to the elaboration of an effective program for the development of tourism in the republic, to the adoption of productive managerial decisions in the field of tourism in the region, and to optimization of the geography of the tourist flows.

scholarly journals Geo-Tagged Photo Metadata Processing Method for Beijing Inbound Tourism Flow

2019 ◽  
Vol 8 (12) ◽  
pp. 556
Author(s):  
Wen Chen ◽  
Zhiyun Xu ◽  
Xiaoyao Zheng ◽  
Yonglong Luo
Keyword(s):  
Time Series ◽  
Data Processing ◽  
Data Preprocessing ◽  
Research Data ◽  
Processing Methods ◽  
Flow Prediction ◽  
Tourism Studies ◽  
Tourist Flows ◽  
Data Processing Methods ◽  
Tourist Flow

Technological advances have led to numerous developments in data sources. Geo-tagged photo metadata has provided a new source of mass research data for tourism studies. A series of data processing methods centering on the various types of information contained in geo-tagged photo metadata have thus been proposed; as a result, the development of tourism studies based on such data has advanced. However, an in-depth study of the data processing methods designed to conduct tourist flow prediction based on geo-tagged photo metadata has not yet been conducted. In order to acquire accurate substitutive data regarding inbound flows in cities, this paper introduces and designs several methods, including data screening, text data similarity calculation, geographical location clustering, and time series data modelling, in order to realize a data preprocessing model for inbound tourist flows in cities based on geo-tagged photo metadata. Wherein, the entropy filtering method was introduced to aid in determining whether the data were posted by inbound tourists; whether the inbound persons’ activities were related to tourism was judged through the calculation of tag text similarity; an efficient clustering method based on geographic grid partition was designed for cases in which the tag values were empty; finally, the time series of the inbound tourist flows of a certain region and period were obtained through data statistics and normalization. For the empirical research, Beijing City in China was selected as the research case, after which the feasibility and accuracy of the methods proposed in this paper were verified through data correlation analysis between Flickr data and real statistical yearbook data, as well as analysis of the prediction results based on a machine learning algorithm. The data preprocessing method introduced and designed in this paper provides a reference for the study of geo-tagged photo metadata in the field of tourism flow prediction. These methods can effectively filter out inbound tourist flow data from geotag photo metadata, thus providing a novel, reliable, and low-cost research data source for urban inbound tourism flow forecasting.

scholarly journals Current Obstacles of Business Development in Uzbekistan

2018 ◽  
Author(s):  
Markhabo Saidova
Keyword(s):  
Analytical Method ◽  
Statistical Data ◽  
Business Development ◽  
Agricultural Products ◽  
Econometric Modeling ◽  
Strategy Selection ◽  
Dynamic Changes ◽  
Modeling And Forecasting ◽  
The Republic ◽  
Development Paths

This article refers to the theoretical and practical aspects of business, its development paths and strategy selection in Uzbek economy, the statistical analyses through methods of observation, collection of statistical data, classification, tabulation; and also diagrams and graphs frequently used in presenting data, dynamic changes, comparison and prognosis of indicators of the development of business, including the ways of improvement of private sector through solve the problems in the formation of economy as well as the perspectives of development of business in Uzbekistan. There are also given econometric modeling and forecasting of business development in GDP through analytical method in dynamic lines, OLS method taking into account the share of business in the number of employed in the volume of production of agricultural products, exports of the Republic of Uzbekistan.

scholarly journals The Ukraine and EU trade balance: prediction via various models of time series

2020 ◽  
Vol 73 ◽  
pp. 01020
Author(s):  
Valerii Matskul ◽  
Diana Okara ◽  
Nataliia Podvalna
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Trade Balance ◽  
Additive Model ◽  
Additive Models ◽  
Main Trend ◽  
Random Component ◽  
The European Union ◽  
Seasonal Component ◽  
Modeling And Forecasting

This article is the first to study, simulate and forecast the monthly dynamics of the trade balance between Ukraine and the European Union for the period from 2005 to 2019. In the presented work, three types of models were used for modeling and forecasting: Automated Neural Networks, additive models ARIMA *ARIMAS (Autoregressive integrated moving average with season component) and Holts model with a damped trend. When modeling using the Automated Neural Networks module, various ensembles of networks and neuron activation functions in hidden layers were used. It turned out that Automated Neural Networks have poor prognostic ability (as in the case considered by us, when modeling insufficiently long series of dynamics). Therefore, when modeling and forecasting the dynamics of the Ukraine-EU trade balance, classical (so-called Box-Jenkins) time series models were used. In this case, the time series is divided into several components (in our case, terms): the main trend is the trend, the seasonal component and the random component (the so-called white noise). By smoothing the initial series, a trend was found, and an analysis of the autocorrelation functions revealed a one-year seasonality. Eliminating the trend and the seasonal component, we obtained a random component, which has a Gaussian distribution. This made it possible to apply first the ARIMA* ARIMAS additive model, and then the Holt model of exponential smoothing with a damped trend. Adequate models of Ukraine-EU trade balance dynamics have been obtained, according to which the forecast has been made. A comparative analysis of the models used. The best model was chosen for forecasting, which allowed to get a good forecast (in comparison with actual data).

Analytical survey of the tourism industry in the Yaroslavl region

2015 ◽  
Vol 9 (3) ◽  
pp. 91-98 ◽  
Author(s):  
Вера Жолудева ◽  
Vera Zholudeva ◽  
Надежда Мельниченко ◽  
Nadezhda Melnichenko
Keyword(s):  
Tourism Industry ◽  
Federal State ◽  
Tourism Sector ◽  
Tourist Flows ◽  
Tourist Infrastructure ◽  
Market Trends ◽  
Quantitative Indicators ◽  
Further Development ◽  
Qualitative Characteristics ◽  
Tourist Flow

On the basis of statistical information analysis of the main market trends in the tourism industry of the Yaroslavl region in the context of municipalities is carried out, the dynamics of tourist flows is estimated. Positive dynamics for each of the quantitative indicators characterizing the market of tourist services is noted, which indicates an overall improvement in the tourism sector of the Yaroslavl region. Last years the growth of the municipalities´ contribution in the total tourist flow in the Yaroslavl Region is noted. This also applies to other indicators of development of the tourism industry. At the same time, the qualitative characteristics of the tourist infrastructure, represented by means of accommodation, transport, including roads, places of interest and sightseeing services, indicate the need to modernize most objects and rendering of the state support of development of tourist infrastructure in the region. To determine the prospects of tourism development in the context of municipalities (urban districts and municipal areas) of Yaroslavl region on the basis of state statistical observation and statistics of the territorial body of the Federal State Statistics Service in the Yaroslavl region has been accomplished forecasting basic indicators of activity of collective accommodation facilities and market the tourism industry. In the Yaroslavl region there is great potential for further development of the tourism industry due to its integration with many of the industries. It will contribute to the development of the economy of the region, and will have an impact on adjacent industries, such as transport, food, communications, trade and others.

Methods of increasing the competitiveness of the tourism industry (on the example of the republic of Сrimea)

2017 ◽  
Vol 30 (1) ◽  
pp. 47-54
Author(s):  
А. А. Yanovskaya
Keyword(s):  
Matrix Method ◽  
Tourism Industry ◽  
Tax Revenues ◽  
Tourism Sector ◽  
The Republic ◽  
The Competitiveness Of Enterprises ◽  
Sector Matrix

The article analyzes the tourism industry and its development in view of the various classification types of tourism. Comparative characteristics of tax revenues in the budget of the Republic of Crimea. The model of competitiveness of tourist field. Calculated the competitiveness of enterprises of the tourism sector matrix method.

scholarly journals System for Forecasting COVID-19 Cases Using Time-Series and Neural Networks Models

2021 ◽  
Vol 5 (1) ◽  
pp. 46
Author(s):  
Mostafa Abotaleb ◽  
Tatiana Makarovskikh
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Time Series ◽  
Time Series Models ◽  
Third Wave ◽  
The Third ◽  
Modeling And Forecasting ◽  
Auto Regressive ◽  
The Russian Federation ◽  
R Programming

COVID-19 is one of the biggest challenges that countries face at the present time, as infections and deaths change daily and because this pandemic has a dynamic spread. Our paper considers two tasks. The first one is to develop a system for modeling COVID-19 based on time-series models due to their accuracy in forecasting COVID-19 cases. We developed an “Epidemic. TA” system using R programming for modeling and forecasting COVID-19 cases. This system contains linear (ARIMA and Holt’s model) and non-linear (BATS, TBATS, and SIR) time-series models and neural network auto-regressive models (NNAR), which allows us to obtain the most accurate forecasts of infections, deaths, and vaccination cases. The second task is the implementation of our system to forecast the risk of the third wave of infections in the Russian Federation.

scholarly journals Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Serdar Neslihanoglu
Keyword(s):  
State Space Model ◽  
Additive Model ◽  
Market Model ◽  
Time Varying ◽  
Daily Data ◽  
Forecasting Performance ◽  
Modeling And Forecasting ◽  
Crypto Currency ◽  
Beta Risk ◽  
The Relationship

AbstractThis research investigates the appropriateness of the linear specification of the market model for modeling and forecasting the cryptocurrency prices during the pre-COVID-19 and COVID-19 periods. Two extensions are offered to compare the performance of the linear specification of the market model (LMM), which allows for the measurement of the cryptocurrency price beta risk. The first is the generalized additive model, which permits flexibility in the rigid shape of the linearity of the LMM. The second is the time-varying linearity specification of the LMM (Tv-LMM), which is based on the state space model form via the Kalman filter, allowing for the measurement of the time-varying beta risk of the cryptocurrency price. The analysis is performed using daily data from both time periods on the top 10 cryptocurrencies by adjusted market capitalization, using the Crypto Currency Index 30 (CCI30) as a market proxy and 1-day and 7-day forward predictions. Such a comparison of cryptocurrency prices has yet to be undertaken in the literature. The empirical findings favor the Tv-LMM, which outperforms the others in terms of modeling and forecasting performance. This result suggests that the relationship between each cryptocurrency price and the CCI30 index should be locally instead of globally linear, especially during the COVID-19 period.

Sign in / Sign up

Export Citation Format

Share Document