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Journal articles on the topic 'Passenger clusters'

Author: Grafiati

Published: 6 September 2023

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1

RACHAEL, T., K. SCHUBERT, W. HELLENBRAND, G. KRAUSE, and J. M. STUART. "Risk of transmitting meningococcal infection by transient contact on aircraft and other transport." Epidemiology and Infection 137, no. 8 (2009): 1057–61. http://dx.doi.org/10.1017/s0950268809002398.

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SUMMARYContact tracing of persons with meningococcal disease who have travelled on aeroplanes or other multi-passenger transport is not consistent between countries. We searched the literature for clusters of meningococcal disease linked by transient contact on the same plane, train, bus or boat. We found reports of two clusters in children on the same school bus and one in passengers on the same plane. Cases within each of these three clusters were due to strains that were genetically indistinguishable. In the aeroplane cluster the only link between the two cases was through a single travel e

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Cahigas, Maela Madel L., Ferani E. Zulvia, Ardvin Kester S. Ong, and Yogi Tri Prasetyo. "A Comprehensive Analysis of Clustering Public Utility Bus Passenger’s Behavior during the COVID-19 Pandemic: Utilization of Machine Learning with Metaheuristic Algorithm." Sustainability 15, no. 9 (2023): 7410. http://dx.doi.org/10.3390/su15097410.

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Public utility bus (PUB) systems and passenger behaviors drastically changed during the COVID-19 pandemic. This study assessed the clustered behavior of 505 PUB passengers using feature selection, K-means clustering, and particle swarm optimization (PSO). The wrapper method was seen to be the best among the six feature selection techniques through recursive feature selection with a 90% training set and a 10% testing set. It was revealed that this technique produced 26 optimal feature subsets. These features were then fed into K-means clustering and PSO to find PUB passengers’ clusters. The alg

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Firdaus, Muhammad Iqbal, Reni Dian Octaviani, and Indri Yusnita. "CLASTERING CALON PENUMPANG KERETA CEPAT JAKARTA-BANDUNG." JURNAL MANAJEMEN TRANSPORTASI DAN LOGISTIK 4, no. 2 (2017): 193. http://dx.doi.org/10.25292/j.mtl.v4i2.98.

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This research aims to cluster prospective passenger high speed rail service corridor Jakarta-Bandung to compensate the rapid development Bandung City as one of the favorite tourist destinations for domestic and international visitors. The data analysis Method is using non-hierarchical cluster and sampling technique by random sampling with 280 respondents. The results show that there are three clusters of prospective passenger for high speed rail service with different characteristics. The first clusters are those who depend heavily on their private vehicles, the second cluster which is the lar

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Firdaus, Muhammad Iqbal, Reni Dian Octaviani, and Indri Yusnita. "CLASTERING CALON PENUMPANG KERETA CEPAT JAKARTA-BANDUNG." Jurnal Manajemen Transportasi & Logistik (JMTRANSLOG) 4, no. 2 (2017): 193. http://dx.doi.org/10.54324/j.mtl.v4i2.98.

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This research aims to cluster prospective passenger high speed rail service corridor Jakarta-Bandung to compensate the rapid development Bandung City as one of the favorite tourist destinations for domestic and international visitors. The data analysis Method is using non-hierarchical cluster and sampling technique by random sampling with 280 respondents. The results show that there are three clusters of prospective passenger for high speed rail service with different characteristics. The first clusters are those who depend heavily on their private vehicles, the second cluster which is the lar

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Dell’Asin, Giulia, and Johannes Hool. "Pedestrian Patterns at Railway Platforms during Boarding: Evidence from a Case Study in Switzerland." Journal of Advanced Transportation 2018 (November 13, 2018): 1–11. http://dx.doi.org/10.1155/2018/4079230.

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The boarding/alighting process at railway platforms is an important determinant of the railway system performance and depends on the characteristics of passengers, the layout of the platform, and the rolling stock. This research aims to increase the understanding of the process, providing a methodological approach to model the passengers’ behaviour when boarding at railway platforms. Adequate criteria were selected to define the so called “boarding cluster” and an easy mechanism was developed to select the boarding clusters. Passenger flow data collected at Bern railway station in Switzerland

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Li, Xiaolu, Peng Zhang, and Guangyu Zhu. "DBSCAN Clustering Algorithms for Non-Uniform Density Data and Its Application in Urban Rail Passenger Aggregation Distribution." Energies 12, no. 19 (2019): 3722. http://dx.doi.org/10.3390/en12193722.

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With the emergence of all kinds of location services applications, massive location data are collected in real time. A hierarchical fast density clustering algorithm, DBSCAN(density based spatial clustering of applications with noise) algorithm based on Gauss mixture model, is proposed to detect clusters and noises of arbitrary shape in location data. First, the gaussian mixture model is used to fit the probability distribution of the dataset to determine different density levels; then, based on the DBSCAN algorithm, the subdatasets with different density levels are locally clustered, and at t

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Indah, Indri Cahaya, Mila Nirmala Sari, and Muhammad Halmi Dar. "Application of the K-Means Clustering Agorithm to Group Train Passengers in Labuhanbatu." SinkrOn 8, no. 2 (2023): 825–37. http://dx.doi.org/10.33395/sinkron.v8i2.12260.

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Transportation is an activity of moving things such as humans, animals, plants and goods from one place to another. To be able to implement transportation, we need a means of transportation that suits our needs. For in Indonesia, people are more inclined to land transportation. That's because land transportation already has a lot of vehicles. Land transportation already has many vehicles that can be used, both for private and for the public. Each vehicle has its uses and risks as well. Therefore we will do a data cluster from the trains. We chose the train, because the risk from using the trai

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Wu, Chaohua, and Xingzu Qi. "Short-term Bus Passenger Flow Forecast Based on CNN-BiLSTM." Advances in Engineering Technology Research 5, no. 1 (2023): 448. http://dx.doi.org/10.56028/aetr.5.1.448.2023.

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Effective prediction of urban bus passenger flow is critical for improving urban bus operation efficiency and optimizing the bus network. However, there are some issues with predicting urban bus passenger flow at the moment, such as lack of single eigenvalue consideration and insufficient research depth. In order to improve the short-term prediction accuracy of urban bus passenger flow, this paper proposed a deep learning prediction model that is based on CNN-BiLSTM. Based on historical data of urban bus passenger flow, this paper analyzes the dependence of bus credit card data, clusters the t

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Tang, Liyang, Yang Zhao, Kwok Leung Tsui, Yuxin He, and Liwei Pan. "A Clustering Refinement Approach for Revealing Urban Spatial Structure from Smart Card Data." Applied Sciences 10, no. 16 (2020): 5606. http://dx.doi.org/10.3390/app10165606.

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Facilitated by rapid development of the data-intensive techniques together with communication and sensing technology, we can take advantage of smart card data collected through Automatic Fare Collection (AFC) systems to establish connections between public transit and urban spatial structure. In this paper, with a case study on Shenzhen metro system in China, we investigate the agglomeration pattern of passenger flow among subway stations. Specifically, leveraging inbound and outbound passenger flows at subway stations, we propose a clustering refinement approach based on cluster member stabil

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Mariñas-Collado, Irene, Ana E. Sipols, M. Teresa Santos-Martín, and Elisa Frutos-Bernal. "Clustering and Forecasting Urban Bus Passenger Demand with a Combination of Time Series Models." Mathematics 10, no. 15 (2022): 2670. http://dx.doi.org/10.3390/math10152670.

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The present paper focuses on the analysis of large data sets from public transport networks, more specifically, on how to predict urban bus passenger demand. A series of steps are proposed to ease the understanding of passenger demand. First, given the large number of stops in the bus network, these are divided into clusters and then different models are fitted for a representative of each of the clusters. The aim is to compare and combine the predictions associated with traditional methods, such as exponential smoothing or ARIMA, with machine learning methods, such as support vector machines

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Gu, Donglian, Yixing Wang, Xinzheng Lu, and Zhen Xu. "Probability-Based City-Scale Risk Assessment of Passengers Trapped in Elevators under Earthquakes." Sustainability 15, no. 6 (2023): 4829. http://dx.doi.org/10.3390/su15064829.

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An accurate prediction of the number of passengers trapped in elevators under earthquakes in urban areas is essential for promoting earthquake emergencies. A probability-based city-scale method for assessing the earthquake-induced risk of passenger entrapment in elevators was proposed, in which city-scale time history analysis was performed to simulate the seismic response of building clusters, and the Monte Carlo simulation was conducted to consider the uncertainty of multiple factors, including the mechanical properties of buildings and elevators, the elevator story position, and the spatiot

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Harantová, Veronika, Jaroslav Mazanec, Vladimíra Štefancová, Jaroslav Mašek, and Hana Brůhová Foltýnová. "Two-Step Cluster Analysis of Passenger Mobility Segmentation during the COVID-19 Pandemic." Mathematics 11, no. 3 (2023): 583. http://dx.doi.org/10.3390/math11030583.

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In this paper, we analyse the specific behaviour of passengers in personal transport commuting to work or school during the COVID-19 pandemic, based on a sample of respondents from two countries. We classified the commuters based on a two-step cluster analysis into groups showing the same characteristics. Data were obtained from an online survey, and the total sample size consists of 2000 respondents. We used five input variables, dividing the total sample into five clusters using a two-step cluster analysis. We observed significant differences between gender, status, and car ownership when us

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Rezapour, Mahdi, and Khaled Ksaibati. "The Latent Class Multinomial Logit Model for Modeling Front-Seat Passenger Seatbelt Choice, Considering Seatbelt Status of Driver." Future Transportation 1, no. 3 (2021): 559–69. http://dx.doi.org/10.3390/futuretransp1030029.

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The literature review highlighted the impacts of drivers’ behavior on passengers’ attitudes in the choice of seatbelt usage. However, limited studies have been done to determine those impacts. Studying the passengers’ seatbelt use is especially needed to find out why passengers choose not to buckle up, and consequently it helps decision makers to target appropriate groups. So, this study was conducted to find drivers’ characteristics that might impact the passenger’s seatbelt use, in addition to other passengers’ characteristics themselves. While performing any analysis, it is important to use

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Zhang, Xiaomin, Gohar Azhar, Emmanuel D. Williams, Steven C. Rogers, and Jeanne Y. Wei. "MicroRNA Clusters in the Adult Mouse Heart: Age-Associated Changes." BioMed Research International 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/732397.

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The microRNAs and microRNA clusters have been implicated in normal cardiac development and also disease, including cardiac hypertrophy, cardiomyopathy, heart failure, and arrhythmias. Since a microRNA cluster has from two to dozens of microRNAs, the expression of a microRNA cluster could have a substantial impact on its target genes. In the present study, the configuration and distribution of microRNA clusters in the mouse genome were examined at various inter-microRNA distances. Three important microRNA clusters that are significantly impacted during adult cardiac aging, the miR-17-92, miR-10

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Handoko, Koko. "PENGELOMPOKKAN DATA MINING PADA JUMLAH PENUMPANG DI BANDARA HANG NADIM." Computer Based Information System Journal 6, no. 2 (2018): 60. http://dx.doi.org/10.33884/cbis.v6i2.708.

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The concept of data mining becomes one of the important tools in information management because the existing information has an increasing number. Data mining has many techniques in practice, one of which is the clustering technique which is the process of grouping data into groups so that data exist in the same group have properties as closely as possible. Clustering has many different methods, one of which is K-Means. By using ata mining clustering on traffic activity data taken from Hang Nadim Airport Batam, it can be obtained by grouping passenger based on clusters according to the nature

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Solntsev, Aleksey, Valeriy Zenchenko, Vitaly Guliy, Oyifien Ozaka Francis, Viacheslav Bezymyannyy, and Valentin Silyanov. "The Analytical Approaches and Principles Used for the Purchases of Light Weight and Passenger Vehicles in a Saturated Market." MATEC Web of Conferences 334 (2021): 01025. http://dx.doi.org/10.1051/matecconf/202133401025.

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Wibowo, Arief, Moh Makruf, Inge Virdyna, and Farah Chikita Venna. "Penentuan Klaster Koridor TransJakarta dengan Metode Majority Voting pada Algoritma Data Mining." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 3 (2021): 565–75. http://dx.doi.org/10.29207/resti.v5i3.3041.

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The Covid-19 pandemic has made many changes in the patterns of community activity. Large-Scale Social Restrictions were implemented to reduce the number of transmission of the virus. This clearly affects the mode of transportation. The mode of transportation makes new regulations to reduce the number of passenger capacities in each fleet, for example, TransJakarta services. This study will categorize the TransJakarta corridors before and during the Covid-19 pandemic. The clustering method of K-Means and K-Medoids is used to obtain accurate calculation results. The calculations are performed us

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Kressner, Josephine D., and Laurie A. Garrow. "Lifestyle Segmentation Variables as Predictors of Home-Based Trips for Atlanta, Georgia, Airport." Transportation Research Record: Journal of the Transportation Research Board 2266, no. 1 (2012): 20–30. http://dx.doi.org/10.3141/2266-03.

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This research investigated the influence of demographic and socio-economic factors on air travel demand by using a unique data set purchased from a credit-reporting agency. Linear regression models based on lifestyle segmentation variables were used to predict air passenger trips for Hartsfield–Jackson International Airport in Atlanta, Georgia. The study focused on predicting trips that originated from or terminated at residences in Atlanta's 13-county metropolitan area. The lifestyle regression models were compared with regression models based on income, because the latter were similar to the

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Ruiz Colmenares, Jon Ander, Estibaliz Asua Uriarte, and Inés del Campo. "Driving-Style Assessment from a Motion Sickness Perspective Based on Machine Learning Techniques." Applied Sciences 13, no. 3 (2023): 1510. http://dx.doi.org/10.3390/app13031510.

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Ride comfort improvement in driving scenarios is gaining traction as a research topic. This work presents a direct methodology that utilizes measured car signals and combines data processing techniques and machine learning algorithms in order to identify driver actions that negatively affect passenger motion sickness. The obtained clustering models identify distinct driving patterns and associate them with the motion sickness levels suffered by the passenger, allowing a comfort-based driving recommendation system that reduces it. The designed and validated methodology shows satisfactory result

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Oguntona, Oluwaferanmi, Kay Ploetner, Marcia Urban, Raoul Rothfeld, and Mirko Hornung. "IMPACT OF AIRLINE BUSINESS MODELS, MARKET SEGMENTS AND GEOGRAPHICAL REGIONS ON AIRCRAFT CABIN CONFIGURATIONS." Journal of Air Transport Studies 10, no. 1 (2019): 1–38. http://dx.doi.org/10.38008/jats.v10i1.8.

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Besides the significance of estimating aircraft seat capacity for airline operating cost and yield estimation as well as for the conceptual design of aircraft, airline fleet planning requires an understanding of aircraft cabin configuration. This paper presents the impact of airline business models, market segments in terms of flight distances, and geographical regions on aircraft cabin configuration, i.e. aircraft seat capacities and installed seats per cabin class. Using the historical databases of global low-cost carriers and airline flight schedules between 2000 and 2016, two ABM clusters

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Wijayanto, Y., A. Fauzi, E. Rustiadi, and Syartinilia. "Spatial Patterns Analysis of Jabodetabek Electric Rail Transportation Using Spatial Autocorrelation Approach." IOP Conference Series: Earth and Environmental Science 950, no. 1 (2022): 012082. http://dx.doi.org/10.1088/1755-1315/950/1/012082.

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Abstract This study investigates the density level of the Jabodetabek KRL stations and routes and the spatial pattern of the Jabodetabek KRL. The method used is spatial autocorrelation calculation using the Moran’s Index putting on data PT KCI from 2014 through 2020, spatial data from BIG, and BPS population data. The study results show that the stations and the routes were congested. Still, there was a drastic decrease in passengers when the Covid-19 outbreak entered Indonesia in March 2020. There was positive autocorrelation and spatial patterns forming Clusters which means that it is necess

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Frutos-Bernal, Elisa, Ángel Martín del Rey, Irene Mariñas-Collado, and María Teresa Santos-Martín. "An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition." Mathematics 10, no. 7 (2022): 1122. http://dx.doi.org/10.3390/math10071122.

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In recent years, a growing number of large, densely populated cities have emerged, which need urban traffic planning and therefore knowledge of mobility patterns. Knowledge of space-time distribution of passengers in cities is necessary for effective urban traffic planning and restructuring, especially in large cities. In this paper, the inbound ridership in the Barcelona metro is modelled into a three-way tensor so that each element contains the number of passenger in the ith station at the jth time on the kth day. Tucker3 decomposition is used to discover spatial clusters, temporal patterns,

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Sekizuka, Tsuyoshi, Kentaro Itokawa, Tsutomu Kageyama, et al. "Haplotype networks of SARS-CoV-2 infections in theDiamond Princesscruise ship outbreak." Proceedings of the National Academy of Sciences 117, no. 33 (2020): 20198–201. http://dx.doi.org/10.1073/pnas.2006824117.

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TheDiamond Princesscruise ship was put under quarantine offshore Yokohama, Japan, after a passenger who disembarked in Hong Kong was confirmed as a coronavirus disease 2019 case. We performed whole-genome sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) directly from PCR+clinical specimens and conducted a phylogenetic analysis of the outbreak. All tested isolates exhibited a transversion at G11083T, suggesting that SARS-CoV-2 dissemination on theDiamond Princessoriginated from a single introduction event before the quarantine started. Although further spreading might

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Faroqi, Hamed, Mahmoud Mesbah, and Jiwon Kim. "Comparing Sequential with Combined Spatiotemporal Clustering of Passenger Trips in the Public Transit Network Using Smart Card Data." Mathematical Problems in Engineering 2019 (April 14, 2019): 1–16. http://dx.doi.org/10.1155/2019/5070794.

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Smart card datasets in the public transit network provide opportunities to analyse the behaviour of passengers as individuals or as groups. Studying passenger behaviour in both spatial and temporal space is important because it helps to find the pattern of mobility in the network. Also, clustering passengers based on their trips regarding both spatial and temporal similarity measures can improve group-based transit services such as Demand-Responsive Transit (DRT). Clustering passengers based on their trips can be carried out by different methods, which are investigated in this paper. This pape

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Pavlyuk, Dmitry, Nadežda Spiridovska, and Irina Yatskiv (Jackiva). "SPATIOTEMPORAL DYNAMICS OF PUBLIC TRANSPORT DEMAND: A CASE STUDY OF RIGA." Transport 35, no. 6 (2021): 576–87. http://dx.doi.org/10.3846/transport.2020.14159.

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Sustainable urban mobility remains an emerging research topic during last decades. In recent years, the smart card data collection systems have become widespread and many studies have been focused on usage of anonymized data from these systems for better understanding of mobility patterns of Public Transport (PT) passengers. Data-driven mobility patterns can benefit transport planners at strategic, tactical, and operational levels. A particular point of interest is a spatiotemporal dynamics of mobility patterns that highlights transformation of the PT passenger flows over the time continuously

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Seo, Younghoon, Donghyun Lim, Woongbee Son, Yeongmin Kwon, Junghwa Kim, and Hyungjoo Kim. "Deriving Mobility Service Policy Issues Based on Text Mining: A Case Study of Gyeonggi Province in South Korea." Sustainability 12, no. 24 (2020): 10482. http://dx.doi.org/10.3390/su122410482.

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Mobility services facilitate various tasks related to transportation and passenger movements. Because of the Fourth Industrial Revolution, the importance of mobility services has been recognized by many countries. Thus, research is ongoing to provide more convenience to passengers and to obtain more efficient transportation systems. In the Republic of Korea, the officials of Gyeonggi Province are interested in providing an advanced mobility service to its residents; however, they still do not have any specific or detailed policies. This study aimed at deriving the key issues facing mobility se

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Lin, Mu, Zhengdong Huang, Tianhong Zhao, Ying Zhang, and Heyi Wei. "Spatiotemporal Evolution of Travel Pattern Using Smart Card Data." Sustainability 14, no. 15 (2022): 9564. http://dx.doi.org/10.3390/su14159564.

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Automated fare collection (AFC) systems can provide tap-in and tap-out records of passengers, allowing us to conduct a comprehensive analysis of spatiotemporal patterns for urban mobility. These temporal and spatial patterns, especially those observed over long periods, provide a better understanding of urban transportation planning and community historical development. In this paper, we explored spatiotemporal evolution of travel patterns using the smart card data of subway traveling from 2011 to 2017 in Shenzhen. To this end, a Gaussian mixture model with expectation–maximization (EM) algori

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Gemra, Stanisław. "The essence and importance of clusters in the management of transport companies." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 18, no. 11 (2017): 30–33. http://dx.doi.org/10.24136/atest.2017.043.

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The aim of the paper is to show the structure of the cluster, the assumptions embedded in the concept car transport companies and to present their own research in the field of express willingness to join the cluster and create a new cluster of passenger transport by Automotive Communications Enterprise. Based on the results presented in the article surveys, it should be noted that the car transport companies show a high level of interest in cooperation with other actors in the sector in the form of the cluster.

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Enin, D. V. "Approaches to Determining the Regular Transit Route Duplication Level." World of Transport and Transportation 19, no. 1 (2021): 210–28. http://dx.doi.org/10.30932/1992-3252-2021-19-1-210-228.

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Issues of duplication of regular transit routes are of particular importance in the field of transport services provided to population and organisation of passenger transportation from the perspective of ensuring compliance with passengers needs for transportation and of the effects of route duplication on the technical, operational, and economic indicators of performance of these routes and the integral route network.In Russia duplication of regular routes within route networks emerged in the late 1990s – early 2000s in urban transit, other transit modes, and in interconnected transit. In the

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Lin, Pengfei, Jiancheng Weng, Dimitrios Alivanistos, Siyong Ma, and Baocai Yin. "Identifying and Segmenting Commuting Behavior Patterns Based on Smart Card Data and Travel Survey Data." Sustainability 12, no. 12 (2020): 5010. http://dx.doi.org/10.3390/su12125010.

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Understanding commuting patterns could provide effective support for the planning and operation of public transport systems. One-month smart card data and travel behavior survey data in Beijing were integrated to complement the socioeconomic attributes of cardholders. The light gradient boosting machine (LightGBM) was introduced to identify the commuting patterns considering the spatiotemporal regularity of travel behavior. Commuters were further divided into fine-grained clusters according to their departure time using the latent Dirichlet allocation model. To enhance the interpretation of th

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Rahmanov, Farhad, Lala Neymatova Lala Neymatova, Ramilya Aliyeva, and Albina Hashimova. "Management of the Transport Infrastructure of Global Logistics: Cross-Country Analysis." Marketing and Management of Innovations 13, no. 4 (2022): 65–75. http://dx.doi.org/10.21272/mmi.2022.4-07.

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In modern society, there is a constant development and improvement of the transport industry, due to which the role and distribution of this logistics industry, which is a service, is growing for the high-quality and fast delivery of goods. To maximize the export of finished products and more effective penetration into international markets around the world are organized by global logistics systems. This article summarizes the arguments and counterarguments within the scientific discussion on the place and prospects of management of the transport infrastructure of global logistics. The study’s

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Maulit, A., A. S. Tlebaldinova, A. B. Nugumanova, and Ye M. Baiburin. "Computer Modelling of Temporal Networks for Bike Sharing Usage Patterns Analysis." Izvestiya of Altai State University, no. 4(114) (September 9, 2020): 102–7. http://dx.doi.org/10.14258/izvasu(2020)4-16.

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This paper presents the results of analyzing the time load of stations in bike-sharing systems using temporal networks. Temporal networks have many applications in the study of the behavior of complex dynamic systems that have a network structure. In particular, they can be used to analyze and predict many dynamic indicators of transport networks, for example, such as the intensity of transport and passenger flows, traffic congestion, capacity of transport nodes, turnover of vehicles, etc. In this work, the indicators of the centrality of stations and clusters of a bike-sharing network are est

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Natalia, Bonifasia Ekta Fima. "Airline Collocation: Frequency Based Analysis with COCA as a Corpus." JET ADI BUANA 8, no. 01 (2023): 55–68. http://dx.doi.org/10.36456/jet.v8.n01.2023.7099.

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Collocations are words that co-occur together in any text and have definite association. The use of collocations is part of linguistic awareness which defines how language is used naturally. This study aims to analyze the collocations used in airlines by using Corpus of Contemporary American English (COCA). The data were analyzed both quantitatively and qualitatively. Quantitatively, the data were calculated regarding the frequency, topics and cluster. Qualitatively, the data were verbally analyzed, described, and discussed. The big data is taken from 1990-2019. The frequent words in area of a

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Dewulf, Wouter, Hilde Meersman, and Eddy Van de Voorde. "FROM CARPET SELLERS TO CARGO STARS: ANALYZING STRATEGIES OF AIR CARGO CARRIERS." Journal of Air Transport Studies 5, no. 1 (2014): 96–119. http://dx.doi.org/10.38008/jats.v5i1.75.

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While some research has been done on passenger airlines strategy, the strategies of air cargo carriers have hardly been researched. This paper analyses and compares the strategies of air cargo carriers. Therefore, a typology of management strategies for both combination and full cargo airlines has been developed, in which the various strategy choices within the strategic framework of the respective air cargo carriers are further elaborated. The typology has been developed through a K-means cluster analysis on a data set of 47 air cargo carriers. The use of a cluster analysis to group the strat

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Bychkova, A. A. "Optimisation of Russian railways’ high-speed routes in the regions." Vestnik Universiteta 1, no. 7 (2022): 82–89. http://dx.doi.org/10.26425/1816-4277-2022-7-82-89.

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Rail transport is constantly in development and improvement, as it is one of the most important strategic means of transportation. That is why the optimization of Russian railway routes in this case is an integral element of development. The introduction of a high-speed passenger transportation route makes it possible to increase throughput capacity, improve service conditions, and strengthen the position in the industry. The article points out the necessity of optimising the route from the Ural to the Volga federal districts. The relevance of the topic under study lies in the advantage of rai

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Tang, Hongjiu. "Regional Patterns and Hierarchical Tendencies: Analysis of the Network Connectivity of 63 Service-Oriented Tourist Cities in China." Sustainability 12, no. 16 (2020): 6532. http://dx.doi.org/10.3390/su12166532.

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Previous studies of service-oriented tourist city networks have often focused on the analysis of the geographical distributions and service roles of important cities instead of the connections and hierarchical tendencies between different types of cities within a whole region. The current study uses big data approaches for the regional connections of 38 tourism organizations, including famous hotels, air passenger transport services, and tourism service agencies, across 63 of the most important tourist cities in China. Fuzzy c-means clustering analysis is used to define eight city arena cluste

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GEGOV, EMIL, M. NADIA POSTORINO, MARK ATHERTON, and FERNAND GOBET. "COMMUNITY STRUCTURE DETECTION IN THE EVOLUTION OF THE UNITED STATES AIRPORT NETWORK." Advances in Complex Systems 16, no. 01 (2013): 1350003. http://dx.doi.org/10.1142/s0219525913500033.

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This paper investigates community structure in the US Airport Network as it evolved from 1990 to 2010 by looking at six bi-monthly intervals in 1990, 2000 and 2010, using data obtained from the Bureau of Transportation Statistics of the US Department of Transport. The data contained monthly records of origin–destination pairs of domestic airports and the number of passengers carried. The topological properties and the volume of people traveling are both studied in detail, revealing high heterogeneity in space and time. A recently developed community structure detection method, accounting for t

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Goldsberry, Leah, and Adam R. Scavette. "Exploiting a Natural Hub: Turning a Stopover into a Destination." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 23 (2018): 8–14. http://dx.doi.org/10.1177/0361198118758983.

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In the mature aviation system of today, it is difficult to establish new hubs that focus solely on transfer traffic. This paper identifies a new type of hub—a natural tourism hub—one at which an airline and the surrounding metropolitan area can simultaneously benefit from a transportation hub and accompanying tourist destination, respectively. The study aims to identify existing airports for these stopover locations that are located on highly trafficked international flight routes. Using Iceland as an example, this country’s success in optimizing its stopover location to promote tourism and ga

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Vallet, Flore, Mostepha Khouadjia, Ahmed Amrani, and Juliette Pouzet. "DESIGNING A DATA VISUALISATION AND ANALYSIS TOOL FOR SUPPORTING DECISION-MAKING WITH PUBLIC TRANSPORTATION NETWORK." Proceedings of the Design Society 1 (July 27, 2021): 1093–102. http://dx.doi.org/10.1017/pds.2021.109.

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AbstractMassive data are surrounding us in our daily lives. Urban mobility generates a very high number of complex data reflecting the mobility of people, vehicles and objects. Transport operators are primary users who strive to discover the meaning of phenomena behind traffic data, aiming at regulation and transport planning. This paper tackles the question "How to design a supportive tool for visual exploration of digital mobility data to help a transport analyst in decision making?” The objective is to support an analyst to conduct an ex post analysis of train circulation and passenger flow

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Il Kim, Kwang, and Keon Myung Lee. "Mining of missing ship trajectory pattern in automatic identification system." International Journal of Engineering & Technology 7, no. 2.12 (2018): 167. http://dx.doi.org/10.14419/ijet.v7i2.12.11117.

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Background/Objectives: Ship trajectories in Vessel Traffic Service (VTS) system are generated by integrating the Automatic Identification System (AIS) or Radar system. However, the AIS system has missing data section caused by AIS device problems, radio jamming, and so on. These data have been confusing ship navigators and VTS operators.Methods/Statistical analysis: In order to extract missing AIS data, time intervals of sequent points from each ship trajectory are calculated. The section with missing AIS data is above a threshold time limit defined by characteristics. Using k-means algorithm,

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Markov, Leonid S., and Vasiliy S. Plotnikov. "Cluster approach and tourism development in the Novosibirsk region." World of Economics and Management 20, no. 4 (2020): 5–24. http://dx.doi.org/10.25205/2542-0429-2020-20-4-5-24.

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The study focuses on the main trends in the tourism industry of the Novosibirsk region. It is shown that the regional industry is developing in line with the national trends and falls with the general development trends of domestic and inbound tourism set forth in the documents of strategic development at the federal and sub-federal levels. The article discusses the aspects of the tourism industry, which determine the specifics of its functioning related to the geographical concentration, heterogeneity, and multiplicity of participants as well as the complex nature of the tourist product. It i

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Тлегенов and B. Tlegenov. "The analysis of the indices verify cluster solutions." Modeling of systems and processes 6, no. 4 (2014): 65–69. http://dx.doi.org/10.12737/4051.

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Jivaramonaikul, Thananan, Pilailuk Akkapaiboon Okada, Nuengruethai Srisong, Watcharee Kanchana-udom, and Pantila Taweewigyakarn. "Investigation of a COVID-19 Cluster Suspected In-flight Transmission, December 2020." Outbreak, Surveillance, Investigation & Response (OSIR) Journal 16, no. 1 (2023): 7–13. http://dx.doi.org/10.59096/osir.v16i1.262096.

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On 1 Dec 2020, the Thai Department of Disease Control was notified of five COVID-19 infections among passengers on a flight from Switzerland to Thailand. The objectives of this investigation were to confirm the outbreak, describe epidemiological characteristics, and identify the source of infection. We performed a descriptive study and contact tracing among the flight’s passengers. We interviewed the cases and reviewed their medical records, as well as an environmental survey of the state quarantine facility. Whole genome sequencing to determine the percentage alignment identity for RT-PCR-pos

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Carcellar III, B. G., A. C. Blanco, and M. Nagai. "SPATIAL AND TEMPORAL COMMUNITY DETECTION OF CAR MOBILITY NETWORK IN METRO MANILA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W19 (December 23, 2019): 101–8. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w19-101-2019.

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Abstract. Transportation Network Companies (TNCs) like Uber utilize GPS and wireless connection for passenger pickup, driver navigation, and passenger drop off. Location-based information from Uber in aggregated form has been made publicly available. They capture instantaneous traffic situation of an area, which makes describing spatiotemporal traffic characteristics of the area possible. Such information is valuable, especially in highly urbanized areas like Manila that experience heavy traffic. In this research, a methodology for identifying the underlying city structure and traffic patterns

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Stapleton, Drew, Melissa Cooley, Darlene Goehner, and Daloud Jandal. "The case for U.S. high speed rail." Journal of Transportation Management 13, no. 1 (2002): 29–40. http://dx.doi.org/10.22237/jotm/1017619500.

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High-speed rail is a form of self-guided ground transportation, which utilizes steel-wheels or magnetic levitation (i.e., Maglev) and can travel in excess of 200 miles per hour. High-speed ground transportation (i.e., HSGT) has been widely used in Europe and Asia, but the debate continues over the usefulness of high-speed rail in the United States. Several metropolitan areas in the United States have been identified as corridors that would benefit from HSGT. High speed rail can offer an alternative or a compliment to over-the-road and air transportation. Initial investment cost for this mode o

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O'Toole, Áine, Verity Hill, Oliver G. Pybus, et al. "Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2." Wellcome Open Research 6 (May 19, 2021): 121. http://dx.doi.org/10.12688/wellcomeopenres.16661.1.

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Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the

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Gkoumas, Konstantinos. "Hyperloop Academic Research: A Systematic Review and a Taxonomy of Issues." Applied Sciences 11, no. 13 (2021): 5951. http://dx.doi.org/10.3390/app11135951.

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Hyperloop is a proposed very high-speed ground transportation system for both passenger and freight that has the potential to be revolutionary, and which has attracted much attention in the last few years. The concept was introduced in its modern form relatively recently, yet substantial progress has been made in the past years, with research and development taking place globally, from several Hyperloop companies and academics. This study examined the status of Hyperloop development and identified issues and challenges by means of a systematic review that analyzed 161 documents from the Scopus

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O'Toole, Áine, Verity Hill, Oliver G. Pybus, et al. "Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2 with grinch." Wellcome Open Research 6 (September 17, 2021): 121. http://dx.doi.org/10.12688/wellcomeopenres.16661.2.

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Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the

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Di Loreto, Samantha, Fabio Serpilli, and Valter Lori. "Soundscape Approach in the Seaport of Ancona: A Case Study." Acoustics 4, no. 2 (2022): 492–516. http://dx.doi.org/10.3390/acoustics4020031.

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Today, the art of knowing how to listen is more urgent than ever. The perceptive sound system of the human being is stimulated daily by countless artificial sounds that dominate natural ones. When it comes to the idea of the soundscape, the terminology was initially referred to by composer and environmentalist Raymond Murray Shafer, who defined “soundscape” as a relationship between the ear, humans, built environments, and society. This paper aims to apply the sound landscape approach in the seaport area of Ancona (Italy); a large area, frequented daily by many people, which is divided into pa

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Chen, Chen, and Yuanchang Xie. "Machine Learning for Recognizing Driving Patterns of Drivers of Large Commercial Trucks." Transportation Research Record: Journal of the Transportation Research Board 2517, no. 1 (2015): 18–27. http://dx.doi.org/10.3141/2517-03.

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Commercial large truck crashes are more likely to involve fatalities and significant costs than passenger vehicle crashes are. To reduce fatigue-related crashes of large trucks caused by drivers' irregular work schedules, FMCSA has enforced hours-of-service rules to regulate the activities of drivers of commercial large trucks. The complex influence of drivers' multiday driving activity patterns on crash risk was examined with data collected from two national truckload carriers. A machine learning approach, k-means clustering, was used to classify large truck drivers into 10 clusters according

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