Public Transportation Dynamic Guidance Model and Algorithm

2011 ◽  
Vol 368-373 ◽  
pp. 3113-3116
Author(s):  
Liang Zou ◽  
Ling Xiang Zhu
Keyword(s):  
Travel Time ◽  
Public Transportation ◽  
Computation Time ◽  
A Algorithm ◽  
Travel Costs ◽  
Computational Performance ◽  
Key Factor ◽  
Straight Line Distance ◽  
Average Computation Time ◽  
Guidance Model

The current public transportation guidance models are static and based on travel times, travel distance and travel costs. However latest survey shows that travel time has become the key factor for passenger travel route selection in big cities. Dynamic public transportation guidance model based on travel time and waiting time was proposed and the effectiveness of this model is proved in this paper. To solve this model efficiently, this paper proposed the application of A* algorithm in dealing with this models using straight line distance between two bus stops in electronic maps as Priori knowledge. Finally, the developed model and algorithm were implemented with 50 random OD pairs based on Guangzhou’s public transportation networks (containing 471 public transportation routes and 1040 stops) and Guangzhou’s electronic map. Their computational performance was analyzed experimentally. The result indicates that the models and algorithm proposed in this paper are very efficient. The average computation time of the algorithm proposed in this paper is 0.154s and the average number of nodes selected of this algorithm is 194.2.

scholarly journals Study of Selection of Bus Mode and Rail Train Surabaya – Malang

2020 ◽  
Vol 3 (2) ◽  
pp. 36-44
Author(s):  
Haris Muhammadun ◽  
Sindiah Bagus Mahendra Tama ◽  
Wateno Oetomo ◽  
Sri Wiwoho Mudjanarko
Keyword(s):  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Travel Time ◽  
Logistic Regression Analysis ◽  
Public Transportation ◽  
Travel Costs ◽  
The Difference ◽  
The City ◽  
Selection Of

The need for transportation facilities and infrastructure that is quite large in the city of Surabaya to the city of Malang is the impact of population growth and increased activity in the city. To support economic, social, trade and education activities between the two cities, public transportation facilities are needed that can meet the needs of the community in terms of comfort and safety. Fulfillment of comfort factors in the use of public transportation such as cheap travel costs, speed of travel time, and accuracy of operational schedules, is expected to increase the interest of travelers to use public vehicles more often than private vehicles. The analysis method used, among others, Descriptive Analysis aims to identify the characteristics of users of the Surabaya-Malang and bus modes, then the Logistic Regression Analysis and Binomial Logit Difference Analysis aim to Obtain a model of selection of bus and train modes in the Surabaya-Malang route, then proceed Sensitivity Analysis which aims to determine the sensitivity of the model of the response of the traveler in determining the choice if there is a change in each attribute of the trip. The results of logistic regression analysis and binomial logit difference, it can be concluded that, attribute / variable X2 (travel time) is the attribute / variable that most influences the mode selection. The sensitivity analysis results can be concluded as follows: Sensitivity to travel costs, the possibility of respondents prefer to use the train mode is greater than the bus. Sensitivity to time, the possibility of respondents prefer to use the train mode is greater than the bus. Sensitivity to the departure schedule (headway), the possibility of respondents choosing to use the train mode will be greater than the bus, if the difference in the headway is between 90-165 minutes. However, if the difference in headway is above 165 minutes, then the respondent will switch to choosing the bus mode.

scholarly journals Multi-Modal Route Recommender System for Bangkok Public Transportation

2020 ◽  
Vol 8 (6) ◽  
pp. 1380-1384
Keyword(s):  
Travel Time ◽  
Recommender System ◽  
Public Transportation ◽  
User Satisfaction ◽  
Transportation Network ◽  
A Algorithm ◽  
Rail Line ◽  
Experience Survey ◽  
Under Construction ◽  
Modal Route

Currently, Bangkok has a 151 kilometers service of a rail line, whereas the total plan is 540 kilometers. More rail lines are now under construction and supposed to be done by a few years. Regarding a massive public transportation network, we need a route recommender system to make traveling more efficient. This paper proposes the route recommender system which supports multi modes of transportation in Bangkok, including BTS, MRT, ARL, BMTA bus, and Chaophraya Riverboat. Users can see suggested routes and sort routes by travel time, fare, number of transfer, and overall score. The A* algorithm with the Haversine formula as the heuristic function is used to calculate the possible routes. Then the best route is selected based on the score, which is calculated form four factors: travel time, fare, number of transfer, and distance. The database contains 13,510 stops, and the results show that the system can suggest accurate routes within a few seconds, which is fast enough for all use cases and achieved overall user satisfaction at 84.8% from our user experience survey.

Segmentasi Citra Mri Menggunakan Deteksi Tepi Untuk Identifikasi Kanker Payudara

2017 ◽  
Vol 15 (2) ◽  
pp. 17 ◽  
Author(s):  
Ervina Varijki ◽  
Bambang Krismono Triwijoyo
Keyword(s):  
Breast Cancer ◽  
Edge Detection ◽  
Object Segmentation ◽  
Computation Time ◽  
Input Image ◽  
Boundary Line ◽  
Cancer Breast ◽  
Average Computation Time ◽  
Breast Cancer Mri ◽  
Image Format

One type of cancer that is capable identified using MRI technology is breast cancer. Breast cancer is still the leading cause of death world. therefore early detection of this disease is needed. In identifying breast cancer, a doctor or radiologist analyzing the results of magnetic resonance image that is stored in the format of the Digital Imaging Communication In Medicine (DICOM). It takes skill and experience sufficient for diagnosis is appropriate, andaccurate, so it is necessary to create a digital image processing applications by utilizing the process of object segmentation and edge detection to assist the physician or radiologist in identifying breast cancer. MRI image segmentation using edge detection to identification of breast cancer using a method stages gryascale change the image format, then the binary image thresholding and edge detection process using the latest Robert operator. Of the20 tested the input image to produce images with the appearance of the boundary line of each region or object that is visible and there are no edges are cut off, with the average computation time less than one minute.

scholarly journals A Choice Too Far: Transit Difficulty and Early High School Transfer

2020 ◽  
pp. 0013189X2094950 ◽  
Author(s):  
Marc L. Stein ◽  
Julia Burdick-Will ◽  
Jeffrey Grigg
Keyword(s):  
High School ◽  
Travel Time ◽  
Administrative Data ◽  
Public Transportation ◽  
School System ◽  
Ninth Grade ◽  
Public School System ◽  
Baltimore City ◽  
School Transfer ◽  
The Relationship

The challenge of a long and difficult commute to school each day is likely to wear on students, leading some to change schools. We used administrative data from approximately 3,900 students in the Baltimore City Public School System in 2014–2015 to estimate the relationship between travel time on public transportation and school transfer during the ninth grade. We show that students who have relatively more difficult commutes are more likely to transfer than peers in the same school with less difficult commutes. Moreover, we found that when these students change schools, their newly enrolled school is substantially closer to home, requires fewer vehicle transfers, and is less likely to have been included among their initial set of school choices.

Estimating Express Train Preference of Urban Railway Passengers Based on Extreme Gradient Boosting (XGBoost) using Smart Card Data

2021 ◽  
pp. 036119812110133
Author(s):  
Eun Hak Lee ◽  
Kyoungtae Kim ◽  
Seung-Young Kho ◽  
Dong-Kyu Kim ◽  
Shin-Hyung Cho
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Public Transportation ◽  
Gradient Boosting ◽  
Log Data ◽  
Smart Card Data ◽  
Extreme Gradient Boosting ◽  
Express Train ◽  
Total Travel Time ◽  
The Individual

As the share of public transport increases, the express strategy of the urban railway is regarded as one of the solutions that allow the public transportation system to operate efficiently. It is crucial to express the urban railway’s express strategy to balance a passenger load between the two types of trains, that is, local and express trains. This research aims to estimate passengers’ preference between local and express trains based on a machine learning technique. Extreme gradient boosting (XGBoost) is trained to model express train preference using smart card and train log data. The passengers are categorized into four types according to their preference for the local and express trains. The smart card data and train log data of Metro Line 9 in Seoul are combined to generate the individual trip chain alternatives for each passenger. With the dataset, the train preference is estimated by XGBoost, and Shapley additive explanations (SHAP) is used to interpret and analyze the importance of individual features. The overall F1 score of the model is estimated to be 0.982. The results of feature analysis show that the total travel time of the local train feature is found to substantially affect the probability of express train preference with a 1.871 SHAP value. As a result, the probability of the express train preference increases with longer total travel time, shorter in-vehicle time, shorter waiting time, and few transfers on the passenger’s route. The model shows notable performance in accuracy and provided an understanding of the estimation results.

Intensities and travel times of seismic rays in a sphere with a linear velocity function

1977 ◽  
Vol 67 (1) ◽  
pp. 33-42
Author(s):  
Mark E. Odegard ◽  
Gerard J. Fryer
Keyword(s):  
Velocity Profile ◽  
Travel Time ◽  
Upper Mantle ◽  
Intensity Ratio ◽  
Computation Time ◽  
Spherical Body ◽  
Travel Times ◽  
Velocity Function ◽  
Intensity Ratios ◽  
Distance Travel

Abstract Equations are presented which permit the calculation of distances, travel times and intensity ratios of seismic rays propagating through a spherical body with concentric layers having velocities which vary linearly with radius. In addition, a method is described which removes the infinite singularities in amplitude generated by second-order discontinuities in the velocity profile. Numerical calculations involving a reasonable upper mantle model show that the standard deviations of the errors for distance, travel time and intensity ratio are 0.0046°, 0.057 sec, and 0.04 dB, respectively. Computation time is short.

A STRUCTURAL APPROACH TO ON-LINE CHARACTER RECOGNITION: SYSTEM DESIGN AND APPLICATIONS

1991 ◽  
Vol 05 (01n02) ◽  
pp. 311-335 ◽  
Author(s):  
FATHALLAH NOUBOUD ◽  
RÉJEAN PLAMONDON
Keyword(s):  
Character Recognition ◽  
Computation Time ◽  
Experimental Tests ◽  
Recognition System ◽  
Structural Approach ◽  
Chain Code ◽  
String Comparison ◽  
Average Computation Time ◽  
On Line ◽  
A Chain

This paper presents a real-time constraint-free handprinted character recognition system based on a structural approach. After the preprocessing operation, a chain code is extracted to represent the character. The classification is based on the use of a processor dedicated to string comparison. The average computation time to recognize a character is about 0.07 seconds. During the learning step, the user can define any set of characters or symbols to be recognized by the system. Thus there are no constraints on the handprinting. The experimental tests show a high degree of accuracy (96%) for writer-dependent applications. Comparisons with other system and methods are discussed. We also present a comparison between the processor used in this system and the Wagner and Fischer algorithm. Finally, we describe some applications of the system.

Computer-assisted Diagnosis for Early Stage Pleural Mesothelioma

2007 ◽  
Vol 46 (03) ◽  
pp. 324-331 ◽  
Author(s):  
P. Jäger ◽  
S. Vogel ◽  
A. Knepper ◽  
T. Kraus ◽  
T. Aach ◽  
...  
Keyword(s):  
Early Stage ◽  
Computation Time ◽  
Hounsfield Unit ◽  
Computer Assisted ◽  
Clinical Test ◽  
Pleural Mesothelioma ◽  
Data Sets ◽  
Data Set ◽  
Average Computation Time ◽  
Ct Data

Summary Objectives: Pleural thickenings as biomarker of exposure to asbestos may evolve into malignant pleural mesothelioma. Foritsearly stage, pleurectomy with perioperative treatment can reduce morbidity and mortality. The diagnosis is based on a visual investigation of CT images, which is a time-consuming and subjective procedure. Our aim is to develop an automatic image processing approach to detect and quantitatively assess pleural thickenings. Methods: We first segment the lung areas, and identify the pleural contours. A convexity model is then used together with a Hounsfield unit threshold to detect pleural thickenings. The assessment of the detected pleural thickenings is based on a spline-based model of the healthy pleura. Results: Tests were carried out on 14 data sets from three patients. In all cases, pleural contours were reliably identified, and pleural thickenings detected. PC-based Computation times were 85 min for a data set of 716 slices, 35 min for 401 slices, and 4 min for 75 slices, resulting in an average computation time of about 5.2 s per slice. Visualizations of pleurae and detected thickeningswere provided. Conclusion: Results obtained so far indicate that our approach is able to assist physicians in the tedious task of finding and quantifying pleural thickenings in CT data. In the next step, our system will undergo an evaluation in a clinical test setting using routine CT data to quantifyits performance.

scholarly journals Improving ozone profile retrieval from spaceborne UV backscatter spectrometers using convergence behaviour diagnostics

2010 ◽  
Vol 3 (6) ◽  
pp. 1555-1568 ◽  
Author(s):  
B. Mijling ◽  
O. N. E. Tuinder ◽  
R. F. van Oss ◽  
R. J. van der A
Keyword(s):  
Cross Sections ◽  
A Priori ◽  
Computation Time ◽  
External Input ◽  
Computational Time ◽  
Ozone Profile ◽  
Global Performance ◽  
Convergence Behaviour ◽  
Low Cloud ◽  
Average Computation Time

Abstract. The Ozone Profile Algorithm (OPERA), developed at KNMI, retrieves the vertical ozone distribution from nadir spectral satellite measurements of back scattered sunlight in the ultraviolet and visible wavelength range. To produce consistent global datasets the algorithm needs to have good global performance, while short computation time facilitates the use of the algorithm in near real time applications. To test the global performance of the algorithm we look at the convergence behaviour as diagnostic tool of the ozone profile retrievals from the GOME instrument (on board ERS-2) for February and October 1998. In this way, we uncover different classes of retrieval problems, related to the South Atlantic Anomaly, low cloud fractions over deserts, desert dust outflow over the ocean, and the intertropical convergence zone. The influence of the first guess and the external input data including the ozone cross-sections and the ozone climatologies on the retrieval performance is also investigated. By using a priori ozone profiles which are selected on the expected total ozone column, retrieval problems due to anomalous ozone distributions (such as in the ozone hole) can be avoided. By applying the algorithm adaptations the convergence statistics improve considerably, not only increasing the number of successful retrievals, but also reducing the average computation time, due to less iteration steps per retrieval. For February 1998, non-convergence was brought down from 10.7% to 2.1%, while the mean number of iteration steps (which dominates the computational time) dropped 26% from 5.11 to 3.79.

scholarly journals 170 Social and Environmental Benefits of Virtual Fracture Clinics in Trauma and Orthopaedic Surgery: Reduced Patient Travel Time, Patient Cost and Air Pollutant Emissions

2021 ◽  
Vol 108 (Supplement_6) ◽  
Author(s):  
J Fort ◽  
H Hughes ◽  
U Khan ◽  
A Glynn
Keyword(s):  
Travel Time ◽  
Fuel Consumption ◽  
Travel Distance ◽  
Air Pollutant ◽  
Environmental Benefits ◽  
Pollutant Emissions ◽  
Patient Cost ◽  
Travel Costs ◽  
Patient Travel ◽  
Travel Burden

Abstract Aim Several papers have analysed the clinical benefits and safety of Virtual Fracture Clinics (VFCs). A significant increase in the use of Trauma and Orthopaedic (T&O) VFCs was seen during the COVID-19 pandemic. This study aims to investigate the social impact of VFCs on the travel burden and travel costs of T&O patients, as well as the potential environmental benefits in relation to fuel consumption and travel-related pollutant emissions. Method All patients referred for T&O VFC review from March 2020 to June 2020 were retrospectively analysed. The travel burden and environmental impacts of hypothetical face-to-face consultations were compared with these VFC reviews. The primary outcomes measured were patient travel time saved, patient travel distance saved, patient cost savings and reduction in air-pollutant emissions. Results Over a four-month period, 1359 VFC consultations were conducted. The average travel distance saved by VFC review was 88.6 kilometres (range 3.3-615), with an average of 73 minutes (range 9-390) of travel-time saved. Patients consumed, on average, 8.2 litres (range 0.3-57.8) less fuel and saved an average of €11.02 (range 0.41-76.59). The average reduction in air-pollutant vehicle emissions, including carbon dioxide, carbon monoxide, nitric oxides and volatile organic compounds was 20.3 kilograms (range 0.8-140.8), 517.3 grams (g) (range 19.3-3592.3), 38.1g (range 1.4-264.8) and 56.9g (range 2.1-395.2), respectively. Conclusions VFCs reduce patient travel distance, travel time and travel costs. In addition, VFCs confer significant environmental benefits through reduced fuel consumption and reduction of harmful environmental emissions.

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