scholarly journals Predictive Model of Air Transportation Management Based on Intelligent Algorithms of Wireless Network Communication

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jiezhuoma La ◽  
Cees Bil ◽  
Iryna Heiets ◽  
Ken Anon Lau
Keyword(s):  
Growth Rate ◽  
Wireless Network ◽  
Air Transportation ◽  
Network Communication ◽  
Intelligent Algorithm ◽  
Single Model ◽  
Transportation Management ◽  
Passenger Traffic ◽  
Model Method ◽  
Combination Forecasting

Due to the numerous factors that affect the air passenger traffic in the air transportation market and the randomness of various factors, in addition, the relationship between it and the air passenger traffic is very complicated, so the air passenger traffic forecast in the air transportation market has always been difficult to solve problem. This research mainly discusses the prediction model of air transportation management based on the intelligent algorithm of wireless network communication. This article uses the wireless network communication intelligent algorithm, comprehensively considers the influence of the GDP growth rate, population growth rate, total import and export volume, and other factors on the air transportation market, and draws a relatively complete forecasting model of aviation business volume. In this paper, we use an equal-weight method, linear combination model method, and Bayesian combination model method when selecting the combination forecasting method (these three methods). Because of the parallelism, robustness, nonlinearity, and other characteristics of the Bayesian network method, it adapts to the complex and highly nonlinear characteristics between air passenger traffic and its influencing factors. In the comprehensive prediction of the single model, the different information contained in the single model is used to achieve different combined prediction effects. The economic information and forecasting angle of the system can reduce systematic forecasting errors and optimize the prognostic results, which can make us more intuitively understand the difference of forecasting results brought by different combination forecasting methods. The Theil inequality coefficient of the ARIMA model is 0.004874, and the average absolute percentage error is 0.005914. This research will play a certain guiding role in the development of China’s civil aviation industry.

scholarly journals Autonomous Mobile Learning Model of Cloud Education Based on Intelligent Algorithm of Wireless Network Communication

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Lin Chen ◽  
Weiping Zhu
Keyword(s):  
Wireless Communication ◽  
Wireless Network ◽  
Mobile Learning ◽  
Data Transmission ◽  
Communication System ◽  
Colleges And Universities ◽  
The Other ◽  
Network Communication ◽  
Intelligent Algorithm ◽  
Wireless Communication System

The rapid development of a new generation of information technology and its widespread application in colleges and universities have promoted profound changes in campus informatization. On the one hand, wireless campus networks as the main infrastructure of digital campuses are gradually popularized in domestic colleges and universities, expanding the campus information network coverage. This article is aimed at studying the addition of intelligent algorithms to wireless network communications to optimize and build autonomous mobile learning for cloud education. In order for children to communicate with teachers face to face, no matter where they are, this article proposes how to reduce the energy loss in wireless communication and find the best intelligent algorithm to realize the cloud education mobile learning platform. Experimental results show that the transmission delay of the wireless communication system of this method is significantly shorter than that of the other two methods, close to 5%, which speeds up the data transmission speed of the wireless communication system. It can be implemented under time-sensitive conditions and has high practical application value. The wireless network communication system of this method has a low packet loss rate and less wireless network data transmission errors, which is nearly 10% lower than the other two methods, thereby improving the data transmission power of the wireless communication network.

scholarly journals IoV Scenario: Bandwidth Aware Algorithm in Wireless Network Communication Mode

2020 ◽  
pp. 1-1
Author(s):  
Peiying Zhang ◽  
Gagangeet Singh ◽  
Neeraj Kumar ◽  
Mohsen Guizani
Keyword(s):  
Wireless Network ◽  
Network Communication ◽  
Communication Mode

ANALYSIS OF ECONOMIC ACTIVITY OF REGIONAL AIRPORTS OF FRANCE AND REGIONAL AIRPORTS OF THE CENTRAL FEDERAL DISTRICT: DEVELOPMENT OF LOW-COST AIRLINES DESTINATIONS AS A KEY FACTOR IN THE PASSENGER TRAFFIC GROWTH

2021 ◽  
Vol 1 (195) ◽  
pp. 75-87
Author(s):  
V.V. Rublev ◽  
Keyword(s):  
Low Cost ◽  
Federal District ◽  
Air Transportation ◽  
Minimal Impact ◽  
National Budget ◽  
Passenger Traffic ◽  
Central Federal District ◽  
Route Network ◽  
Key Factor ◽  
Regional Airports

The article presents an analysis of the activities of regional airports in France in 2019. The growth of passenger traffic was observed in those airports that actively developed cooperation with budget airlines, increasing the number of destinations in the route network. Regional airports in France, whose route network structure did not expand in 2019, showed a slight decrease in passenger traffic (from –0.1% to –3%). The first and only experimental regional airport in France (city of Beziers), handling flights of only one budget airline, Ryanair, showed an increase in passenger traffic by 14.5% in 2019. The share of routes of budget airlines in the structure of the route network of regional airports in France is quite high. The key problems of regional airports in Russia are the low passenger traffic and the underdeveloped route network. Due to the presence of the only national budget airline "Pobeda" on the market and the minimal impact on the segment of budget air transportation of foreign airlines, the share of budget air transportation destinations in the structure of regional airports of the Russian Federation continues to remain at an extremely low level. 2019 showed a record growth in passenger traffic at regional airports in the Central Federal District (an increase from +2.8% to +262%, with the exception of Tambov Airport, whose passenger traffic fell by 57.4%), which indicates an increase in demand and the need to expand the route network of regional airports. On the example of the Voronezh airport, a model for the development of low-cost airline destinations is presented.

scholarly journals Support Vector Regression Method for Regional Economic Mid- and Long-Term Predictions Based on Wireless Network Communication

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Lingyu Dong
Keyword(s):  
Machine Learning ◽  
Communication Network ◽  
Support Vector Regression ◽  
Wireless Network ◽  
Regression Method ◽  
Network Communication ◽  
Support Vector ◽  
Network Coverage ◽  
Data Packets

In recent years, wireless sensor network technology has continued to develop, and it has become one of the research hotspots in the information field. People have higher and higher requirements for the communication rate and network coverage of the communication network, which also makes the problems of limited wireless mobile communication network coverage and insufficient wireless resource utilization efficiency become increasingly prominent. This article is aimed at studying a support vector regression method for long-term prediction in the context of wireless network communication and applying the method to regional economy. This article uses the contrast experiment method and the space occupancy rate algorithm, combined with the vector regression algorithm of machine learning. Research on the laws of machine learning under the premise of less sample data solves the problem of the lack of a unified framework that can be referred to in machine learning with limited samples. The experimental results show that the distance between AP1 and AP2 is 0.4 m, and the distance between AP2 and Client2 is 0.6 m. When BPSK is used for OFDM modulation, 2500 MHz is used as the USRP center frequency, and 0.5 MHz is used as the USRP bandwidth; AP1 can send data packets. The length is 100 bytes, the number of sent data packets is 100, the gain of Client2 is 0-38, the receiving gain of AP2 is 0, and the receiving gain of AP1 is 19. The support vector regression method based on wireless network communication for regional economic mid- and long-term predictions was completed well.

scholarly journals Airport level of service: A model according to departing passengers’ perceptions at a small-sized airport

2017 ◽  
Vol 7 (1) ◽  
pp. 65 ◽  
Author(s):  
Max Well Elias Gonçalves ◽  
Mauro Caetano
Keyword(s):  
Factor Analysis ◽  
Conceptual Model ◽  
Exploratory Factor Analysis ◽  
Air Transportation ◽  
Service Evaluation ◽  
Three Dimensions ◽  
Level Of Service ◽  
Relative Importance ◽  
Transportation Management ◽  
Management Perspective

Purpose: This study proposes a conceptual model of level of service evaluation to a small-sized airport with a focus on departing passengers.Design/Methodology: The variables selected to compose the model were chosen according to their adequacy to departing passengers and the airport’s characteristics. A survey was conducted, and, posteriorly, exploratory factor analysis was used in order to verify the adequacy of the conceptual model proposed and also to improve it according to the results obtained.Findings: The results show that the level of service of the airport is composed of three dimensions: airport characteristics, passenger processing, and prices. The relative importance of the dimensions according to their contribution to the composition of the airport’s overall level of service was also determined.Originality/value: The paper combines theoretical and practical findings in a model for level of service evaluation to a small-sized airport from an air transportation management perspective.

Sign in / Sign up

Export Citation Format

Share Document