scholarly journals The evolution of Cuba's air transport network in the Embargo Era: 1967–2017

2022 ◽  
Vol 98 ◽  
pp. 103259
Author(s):  
Hilton A. Córdoba
Keyword(s):  
Transport Network ◽  
Air Transport

scholarly journals Robustness of China’s air transport network from 1975 to 2017

2020 ◽  
Vol 539 ◽  
pp. 122876 ◽  
Author(s):  
Yu Chen ◽  
Jiaoe Wang ◽  
Fengjun Jin
Keyword(s):  
Transport Network ◽  
Air Transport

scholarly journals Predicting dengue importation into Europe, using machine learning and model-agnostic methods

2019 ◽  
Author(s):  
Donald Salami ◽  
Carla Alexandra Sousa ◽  
Maria do Rosário Oliveira Martins ◽  
César Capinha
Keyword(s):  
Machine Learning ◽  
Operating Characteristic ◽  
Predictive Accuracy ◽  
Predictive Performance ◽  
Machine Learning Algorithms ◽  
Transport Network ◽  
Air Transport ◽  
Health Concern ◽  
Centrality Measures ◽  
Network Centrality

ABSTRACTThe geographical spread of dengue is a global public health concern. This is largely mediated by the importation of dengue from endemic to non-endemic areas via the increasing connectivity of the global air transport network. The dynamic nature and intrinsic heterogeneity of the air transport network make it challenging to predict dengue importation.Here, we explore the capabilities of state-of-the-art machine learning algorithms to predict dengue importation. We trained four machine learning classifiers algorithms, using a 6-year historical dengue importation data for 21 countries in Europe and connectivity indices mediating importation and air transport network centrality measures. Predictive performance for the classifiers was evaluated using the area under the receiving operating characteristic curve, sensitivity, and specificity measures. Finally, we applied practical model-agnostic methods, to provide an in-depth explanation of our optimal model’s predictions on a global and local scale.Our best performing model achieved high predictive accuracy, with an area under the receiver operating characteristic score of 0.94 and a maximized sensitivity score of 0.88. The predictor variables identified as most important were the source country’s dengue incidence rate, population size, and volume of air passengers. Network centrality measures, describing the positioning of European countries within the air travel network, were also influential to the predictions.We demonstrated the high predictive performance of a machine learning model in predicting dengue importation and the utility of the model-agnostic methods to offer a comprehensive understanding of the reasons behind the predictions. Similar approaches can be utilized in the development of an operational early warning surveillance system for dengue importation.

The Role of Regional Airports in Connectivity and Regional Development

2021 ◽  
Author(s):  
Oscar Díaz Olariaga
Keyword(s):  
Economic Development ◽  
Regional Development ◽  
Socioeconomic Development ◽  
Transport Network ◽  
Air Transport ◽  
Investment Policies ◽  
Air Transport Industry ◽  
Social And Economic Development ◽  
Regional Airports

This article analyzes the contribution of regional airports in Colombia to the development of the domestic air transport network, and with it, to the connectivity of the regions and their social and economic development. The growth and evolution of Colombian regional airports are supported and driven by a set of public and investment policies, designed exclusively for the air sector and implemented, almost continuously, since the liberalization of the air transport industry in the country in the early 1990s and are still in development. Having said this, this work analyzes how the network of regional airports have been able to develop in two and a half decades through public policies, and later, how these airports have positively impacted connectivity and socioeconomic development in the territories. All this is done through the presentation and analysis of related indicators.

The African air transport network

2017 ◽  
pp. 40-60
Author(s):  
Davide Scotti ◽  
Gianmaria Martini ◽  
Stefano Leidi ◽  
Kenneth J. Button
Keyword(s):  
Transport Network ◽  
Air Transport

scholarly journals Evolution and Determinants of an Air Transport Network: A Case Study of the Chinese Main Air Transport Network

2019 ◽  
Vol 11 (14) ◽  
pp. 3933 ◽  
Author(s):  
Min Su ◽  
Weixin Luan ◽  
Zeyang Li ◽  
Shulin Wan ◽  
Zhenchao Zhang
Keyword(s):  
Network Structure ◽  
High Speed ◽  
Information Source ◽  
Small World ◽  
Transport Network ◽  
Air Transport ◽  
Promoting Effect ◽  
High Speed Rail ◽  
Path Lengths ◽  
The Impact

The Chinese main air transport network (CMATN) is the framework for air passenger transport in the country. This study uses complex networks and an econometric model to analyze CMATN’s evolution and determinants. In terms of overall network structure, the network has always shown small-world properties, with smaller average path lengths (2.06–2.15) and larger clustering coefficients (0.68–0.77), while its cumulative degree distribution follows an exponential function. City passenger volumes conform to the degree power law function, which means that the more destinations a city connects to, the higher its passenger traffic will be. In major hub cities, such as Beijing, Shanghai, and Guangzhou, control power decreases, while Chengdu, Kunming, Chongqing, Xi’an, Urumqi, and other cities play an increasingly important role in CMATN. In terms of main route passenger volumes and formation, increases in GDP and tourism have had a promoting effect, while high-speed rail (HSR) poses a threat to overlapping routes. CMATN is primarily located in the central and eastern regions, focusing on China’s economy, tourism, and efficient HSR development. Although the competition from HSR affects the overall network structure of CMATN based on its influence on specific routes, we believe that the impact is limited due to the different transport attributes of the two networks. The research results of this study can become an information source for decision makers and provide a reference for air transport to seek sustainable development.

scholarly journals Modelling performance an air transport network operated by subsonic and supersonic aircraft

2020 ◽  
Vol 124 (1281) ◽  
pp. 1702-1739
Author(s):  
M. Janić
Keyword(s):  
Social Performance ◽  
Economic Feasibility ◽  
Transport Network ◽  
Air Transport ◽  
Analytical Models ◽  
Commercial Aircraft ◽  
Supersonic Aircraft ◽  
Route Network ◽  
Fuel Consumption And Emissions ◽  
The Given

ABSTRACTThis paper deals with modelling the performance of an air transport network operated by existing subsonic and the prospective supersonic commercial aircraft. Analytical models of indicators of the infrastructural, technical/technological, operational, economic, environmental, and social performance of the network relevant for the main actors/stakeholders involved are developed. The models are applied to the given long-haul air route network exclusively operated by subsonic and supersonic aircraft according to the specified “what-if” scenarios.The results from application of the models indicate that supersonic flights powered by LH2 (Liquid Hydrogen) could be more feasible than their subsonic counterparts powered by Jet A fuel, in terms of about three times higher technical productivity, 46% smaller size of the required fleet given the frequency of a single flight per day, 20% lower sum of the aircraft/airline operational, air passenger time, and considered external costs, up to two times higher overall social-economic feasibility, and 94% greater savings in contribution to global warming and climate change. These flights could be less feasible in terms of about 70-85% higher aircraft/airline operational costs, 70% and 19% higher fuel consumption and emissions of Green House Gases, respectively, and 6-13% higher noise compared to the specified acceptable levels.

A Study on Evaluation Method for the International Air Transport Network

1996 ◽  
Vol 13 ◽  
pp. 761-768
Author(s):  
Tetsuo YAI ◽  
Kazuyuki TAKADA
Keyword(s):  
Evaluation Method ◽  
Transport Network ◽  
Air Transport
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