scholarly journals Exploring for Route Preferences of Subway Passengers Using Smart Card and Train Log Data

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Eun Hak Lee ◽  
Kyoungtae Kim ◽  
Seung-Young Kho ◽  
Dong-Kyu Kim ◽  
Shin-Hyung Cho
Keyword(s):  
Shortest Path ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Access Time ◽  
Practical Application ◽  
Shortest Path Algorithm ◽  
Log Data ◽  
Passenger Travel ◽  
Mode Share ◽  
Alternative Routes

As the mode share of the subway in Seoul has increased, the estimation of passenger travel routes has become a crucial issue to identify the congestion sections in the subway network. This paper aims to estimate the travel train of subway passengers in Seoul. The alternative routes are generated based on the train log data. The travel route is then estimated by the empirical cumulative distribution functions (ECDFs) of access time, egress time, and transfer time. The train choice probability is estimated for alternative train combinations and the train combination with the highest probability is assigned to the subway passenger. The estimated result is validated using the transfer gate data which are recorded on private subway lines. The result showed that the accuracy of the estimated travel train is shown to be 95.6%. The choice ratios for no-transfer, one-transfer, two-transfer, three-transfer, and four-transfer trips are estimated to be 53.9%, 37.7%, 6.5%, 1.5%, and 0.4%, respectively. Regarding the practical application, the passenger kilometers by lines are estimated with the travel route estimation of the whole network. As results of the passenger kilometer calculation, the passenger kilometer of the proposed algorithm is estimated to be 88,314 million passenger kilometer. The proposed algorithm estimates the passenger kilometer about 13% higher than the shortest path algorithm. This result implies that the passengers do not always prefer the shortest path and detour about 13% for their convenience.

scholarly journals Methods of Randomization of Large Files with High Volatility

1970 ◽  
Vol 3 (1) ◽  
pp. 79
Author(s):  
Patrick C. Mitchell ◽  
Thomas K. Burgess
Keyword(s):  
Distribution Functions ◽  
Cumulative Distribution ◽  
Direct Access ◽  
Access Time ◽  
Cumulative Distribution Functions ◽  
High Volatility

<p><span>Key-to-address conversion algorithms which have been used for a large, direct access file are compared with respect to record density and access time. Cumulative distribution functions are plotted to demonstrate the distribution of addresses generated by each method. The long-standing practice of counting address collisions is shown to be less valuable in fudging algorithm effectiveness than considering the maximum number of contiguously occupied file locations.</span></p>

The Optimization Shortest Path Algorithm and its Application in Campus Geographic Information System

2012 ◽  
Vol 170-173 ◽  
pp. 2819-2822
Author(s):  
Jing Jing Tang ◽  
Wei Zhong Wu ◽  
Zhen Hu Wang
Keyword(s):  
Information System ◽  
Geographical Information System ◽  
Shortest Path ◽  
System Development ◽  
Geographical Information ◽  
Practical Application ◽  
Constraint Condition ◽  
Shortest Path Algorithm ◽  
Development Platform ◽  
Straight Line

To manage the campus space information effectively, and provide faster query and browse function to user, a straight line optimization algorithm was proposed. The algorithm regards the target node’s situation and direction as constraint condition when searching map nodes in road network. The algorithm can reduce the number of searched nodes and increase system-search velocity. To prove the algorithm’s practical application, a small campus geographical information system is built on a component geographical-information-system development platform. In this system, the algorithm is used to simulate searching the shortest path between two desired nodes. The simulation result indicates that this algorithm can search the path quickly and reliably.

scholarly journals Do galactic bars depend on environment?: an information theoretic analysis of Galaxy Zoo 2

2020 ◽  
Vol 501 (1) ◽  
pp. 994-1001
Author(s):  
Suman Sarkar ◽  
Biswajit Pandey ◽  
Snehasish Bhattacharjee
Keyword(s):  
Spatial Distribution ◽  
Mutual Information ◽  
Local Density ◽  
Statistical Significance ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Host Galaxy ◽  
Data Sets ◽  
Data Set ◽  
Information Theoretic

ABSTRACT We use an information theoretic framework to analyse data from the Galaxy Zoo 2 project and study if there are any statistically significant correlations between the presence of bars in spiral galaxies and their environment. We measure the mutual information between the barredness of galaxies and their environments in a volume limited sample (Mr ≤ −21) and compare it with the same in data sets where (i) the bar/unbar classifications are randomized and (ii) the spatial distribution of galaxies are shuffled on different length scales. We assess the statistical significance of the differences in the mutual information using a t-test and find that both randomization of morphological classifications and shuffling of spatial distribution do not alter the mutual information in a statistically significant way. The non-zero mutual information between the barredness and environment arises due to the finite and discrete nature of the data set that can be entirely explained by mock Poisson distributions. We also separately compare the cumulative distribution functions of the barred and unbarred galaxies as a function of their local density. Using a Kolmogorov–Smirnov test, we find that the null hypothesis cannot be rejected even at $75{{\ \rm per\ cent}}$ confidence level. Our analysis indicates that environments do not play a significant role in the formation of a bar, which is largely determined by the internal processes of the host galaxy.

scholarly journals Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations

2021 ◽  
Vol 13 (6) ◽  
pp. 1096
Author(s):  
Soi Ahn ◽  
Sung-Rae Chung ◽  
Hyun-Jong Oh ◽  
Chu-Yong Chung
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Northeast Asia ◽  
Low Earth Orbit ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Radiometric Calibration ◽  
Climate Data ◽  
Error Statistics ◽  
Spatiotemporal Resolution

This study aimed to generate a near real time composite of aerosol optical depth (AOD) to improve predictive model ability and provide current conditions of aerosol spatial distribution and transportation across Northeast Asia. AOD, a proxy for aerosol loading, is estimated remotely by various spaceborne imaging sensors capturing visible and infrared spectra. Nevertheless, differences in satellite-based retrieval algorithms, spatiotemporal resolution, sampling, radiometric calibration, and cloud-screening procedures create significant variability among AOD products. Satellite products, however, can be complementary in terms of their accuracy and spatiotemporal comprehensiveness. Thus, composite AOD products were derived for Northeast Asia based on data from four sensors: Advanced Himawari Imager (AHI), Geostationary Ocean Color Imager (GOCI), Moderate Infrared Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). Cumulative distribution functions were employed to estimate error statistics using measurements from the Aerosol Robotic Network (AERONET). In order to apply the AERONET point-specific error, coefficients of each satellite were calculated using inverse distance weighting. Finally, the root mean square error (RMSE) for each satellite AOD product was calculated based on the inverse composite weighting (ICW). Hourly AOD composites were generated (00:00–09:00 UTC, 2017) using the regression equation derived from the comparison of the composite AOD error statistics to AERONET measurements, and the results showed that the correlation coefficient and RMSE values of composite were close to those of the low earth orbit satellite products (MODIS and VIIRS). The methodology and the resulting dataset derived here are relevant for the demonstrated successful merging of multi-sensor retrievals to produce long-term satellite-based climate data records.

Utilizing Restricted Direction Strategy and Binary Heap Technology to Optimize Dijkstra Algorithm in WebGIS

2009 ◽  
Vol 419-420 ◽  
pp. 557-560 ◽  
Author(s):  
Rui Li
Keyword(s):  
Shortest Path ◽  
Operating Efficiency ◽  
Dijkstra Algorithm ◽  
Shortest Path Algorithm ◽  
Research Focus ◽  
Network Information ◽  
The Core ◽  
Highway Network ◽  
Core Issue ◽  
Storage Structures

Shortest path is the core issue in application of WebGIS. Improving the efficiency of the algorithm is an urgent requirement to be resolved at present. By the lossy algorithm analyzing, which is the current research focus of the shortest path algorithm to optimize, utilizing adjacency table of storage structures, restricted direction strategy and binary heap technology to optimize the algorithm, thereby reduce the scale of algorithm to improve the operating efficiency of algorithm. This scheme has been applied in the simulation of the data downloaded from the Guangdong Provincial Highway Network Information System and satisfactory results have been obtained.

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