scholarly journals Using Fuzzy Clustering of User Perception to Determine the Number of Level-of-Service Categories for Bus Rapid Transit

2021 ◽  
Vol 23 (2) ◽  
Author(s):  
Yueying Huo ◽  
Jinhua Zhao ◽  
Xiaojuan Li ◽  
Chen Guo
Keyword(s):  
Fuzzy Clustering ◽  
Bus Rapid Transit ◽  
Level Of Service ◽  
Rapid Transit ◽  
User Perception ◽  
Dimension Vector ◽  
Cluster Validity Indices ◽  
Validity Indices ◽  
Four Levels ◽  
Levels Of Service

The concept of level of service (LOS) is meant to reflect user perception of the quality of service provided by a transportation facility or service. Although the LOS of bus rapid transit (BRT) has received considerable attention, the number of levels of service of BRT that a user can perceive still remains unclear. Therefore, in this paper, we address this issue using fuzzy clustering of user perception. User perception is defined as a six-dimension vector of the perceived arrival time, perceived waiting time, bus speed perception, passenger load perception, perceived departure time, and overall perception. A smartphone-based transit travel survey system was developed, with which user perception surveys were conducted in three BRT systems in China. Fuzzy C-Means clustering, improved using a simulated annealing genetic algorithm, was adopted to partition user perception into two to ten clusters. Seven cluster validity indices were used to determine the appropriate number of LOS categories. Our results indicate that users can perceive two to four levels of service.

scholarly journals The Quality of Bus Rapid Transit (BRT) Shelter Services of Mangkang-Penggaron Route in CBD Semarang

2012 ◽  
Vol 8 (1) ◽  
pp. 42 ◽  
Author(s):  
Putri - Mahardhini ◽  
Mardwi - Rahdriawan
Keyword(s):  
Central Business District ◽  
Bus Rapid Transit ◽  
Quality Of Services ◽  
Service Reliability ◽  
Mass Transportation ◽  
Rapid Transit ◽  
User Perception ◽  
Business District ◽  
Shelter Services

ABSTRACTThe Government of Semarang have sought to develop a mass transportation system using theconcept of Bus Rapid Transit (BRT) in Mangkang‐Penggaron corridor. In order to effectivelyfacilitate the movement of city dwellers, the BRT system required the provision of functioningshelters along the corridor. There is a need to optimize the function of the shelters including theintegration to other modes of transportation and to the activities of the Central Business District(CBD), ensuring optimum performance of the whole BRT system. This study determined andevaluated the quality of BRT shelter services in Semarang based on user perception. The studyemployed analysis regarding the fulfillment of criteria for quality of services including waitingtime, convenience, service reliability, distance, and BRT shelter clerk services. The analysisprocesses concluded that the current BRT shelter services were in fact less than ideal. The studyfound lack of maintenance and the need for improvement of services at rush hour.Keywords: evaluation, quality of services, and bus shelter

scholarly journals A novel fuzzy clustering approach to regionalise watersheds with an automatic determination of optimal number of clusters

2017 ◽  
Vol 65 (4) ◽  
pp. 359-365 ◽  
Author(s):  
Javier Senent-Aparicio ◽  
Jesús Soto ◽  
Julio Pérez-Sánchez ◽  
Jorge Garrido
Keyword(s):  
Frequency Analysis ◽  
Fuzzy Clustering ◽  
Optimal Number ◽  
Regional Frequency Analysis ◽  
Cluster Validity ◽  
Number Of Clusters ◽  
Cluster Validity Indices ◽  
Validity Indices ◽  
Homogeneous Regions ◽  
Optimal Number Of Clusters

AbstractOne of the most important problems faced in hydrology is the estimation of flood magnitudes and frequencies in ungauged basins. Hydrological regionalisation is used to transfer information from gauged watersheds to ungauged watersheds. However, to obtain reliable results, the watersheds involved must have a similar hydrological behaviour. In this study, two different clustering approaches are used and compared to identify the hydrologically homogeneous regions. Fuzzy C-Means algorithm (FCM), which is widely used for regionalisation studies, needs the calculation of cluster validity indices in order to determine the optimal number of clusters. Fuzzy Minimals algorithm (FM), which presents an advantage compared with others fuzzy clustering algorithms, does not need to know a priori the number of clusters, so cluster validity indices are not used. Regional homogeneity test based on L-moments approach is used to check homogeneity of regions identified by both cluster analysis approaches. The validation of the FM algorithm in deriving homogeneous regions for flood frequency analysis is illustrated through its application to data from the watersheds in Alto Genil (South Spain). According to the results, FM algorithm is recommended for identifying the hydrologically homogeneous regions for regional frequency analysis.

scholarly journals Development of Fuzzy Level of Service Criteria for Bus Rapid Transit considering User Heterogeneities in China

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yueying Huo ◽  
Jianrong Liu ◽  
Jian Zhang ◽  
Xiaojuan Li
Keyword(s):  
Market Segmentation ◽  
Latent Class ◽  
Latent Class Model ◽  
Wait Time ◽  
Bus Rapid Transit ◽  
Level Of Service ◽  
Rapid Transit ◽  
Fuzzy C Means Clustering ◽  
Survey System ◽  
Transit Market

Level of service (LOS) analysis based on LOS criteria is essential for the planning, design, and operational evaluation of public transit. However, there are no systematic transit LOS criteria at present in China. Bus rapid transit (BRT) is receiving increasing attention worldwide. Therefore, this study addresses LOS criteria for BRT in China. Transit passengers are heterogeneous in their perceptions, needs, and behavior. The traditional hard LOS criteria have an inherent weakness, because of which the accuracy of an LOS analysis is limited. Thus, in this study, we initially conducted transit market segmentation to reduce heterogeneity and subsequently developed BRT fuzzy LOS criteria for different passenger groups. Using a smartphone-based transit travel survey system, we organized BRT passenger travel surveys on three BRT systems in China to collect data. Transit market segmentation was performed based on user perceptions; passengers were segmented into a calm passenger group and an anxious passenger group using the latent class model. Passenger arrival time, passenger wait time, and running speed of the bus were selected as service metrics to reflect the BRT’s LOS. BRT fuzzy LOS criteria for the three service metrics in the case of both the calm and anxious passenger groups were developed using fuzzy C-means clustering. The LOS criteria for the two groups of passengers fit their psychological characteristics and reflected their personalized travel needs. Fuzzy LOS criteria can describe to what extent service metric values belong to the adjacent LOS categories via the use of membership. Thus, fuzzy LOS criteria can overcome the weakness of hard LOS criteria.

Diesel engine injection faults' detection and classification utilizing unsupervised fuzzy clustering techniques

2019 ◽  
Vol 233 (16) ◽  
pp. 5622-5636
Author(s):  
Ezzeddine Ftoutou ◽  
Mnaouar Chouchane
Keyword(s):  
Diesel Engine ◽  
Fuzzy Clustering ◽  
Clustering Algorithms ◽  
Variable Number ◽  
High Detection Rate ◽  
Time Frequency ◽  
Cluster Validity Indices ◽  
Validity Indices ◽  
Number Of Classes ◽  
Unsupervised Fuzzy Clustering

By using the unsupervised fuzzy clustering, this study attempts to design a new scheme for the unsupervised detection and classification of two injection faults using the time–frequency analysis of vibration signals of an internal combustion, four-stroke, diesel engine with six cylinders in-line. To reach this objective, two new methods called modified S-transform and two-dimensional non-negative matrix factorization are used. Three fuzzy clustering algorithms and nine cluster validity indices, for a variable number of classes, are also used to detect and classify the fault classes. The implementation of these methods resulted in a high detection rate of the injection faults.

Bus Rapid Transit (BRT) Users’ Discernment in Lagos Megacity: Lesson from Primero Transport Service

2020 ◽  
Author(s):  
Fariha Azalea
Keyword(s):  
Factor Analysis ◽  
Service Quality ◽  
Travel Behavior ◽  
Decision Makers ◽  
Bus Rapid Transit ◽  
Level Of Service ◽  
Rapid Transit ◽  
Transport Service ◽  
Transport Services ◽  
Mode Of Operation

The study examines Bus Rapid Transit (BRT) users’ perspicacity in Lagos, Nigeria along Ikorodu-Mile12 Bus Rapid Transit (BRT) corridor in order to guide, provide information for policies and decision makers during policies formulation. This study assesses the socio-economic character of passengers using the primer transport service along Ikorodu-Mile 12 BRT corridor; analysed the travel behavior of commuters using the primero transport service in the study area and examine the commuters’ perspicacity and expectation on the level of service quality provided by Primero Transport Service. A total of three hundred ninety-four (394) commuters (one commuter per bus) who go back and forth through the buses were sampled. Perception and expectation about service were asked. The result of factor analysis found that commuters were satisfy with the service offer by Primero, physical appearance, level of clean, mode of operation and level of service deliver by Primero transport services.

Understanding Platform Overcrowding at Bus Rapid Transit Stations

2015 ◽  
Vol 2533 (1) ◽  
pp. 118-123 ◽  
Author(s):  
Nicolae Duduta ◽  
Asis Subedi
Keyword(s):  
Latin American ◽  
Bus Rapid Transit ◽  
Level Of Service ◽  
Predictive Equation ◽  
Rapid Transit ◽  
Microscopic Simulation ◽  
Different Types ◽  
Simulation Results ◽  
Specific Volumes ◽  
Main Entrance

Platform overcrowding is a very common but relatively poorly understood occurrence at most bus rapid transit (BRT) systems in cities in the developing world. Most literature on BRT capacity focuses on vehicle throughput for different types of lane and station configurations; relatively little is known about how different station layouts handle specific volumes of boarding and alighting passengers. In this paper, this gap in knowledge was addressed by building a microscopic simulation model to test the ability of a typical Latin American BRT station (median, high-platform, one bus bay per direction) to handle various volumes of passengers under different scenarios. With this modeling exercise, areas in a station most likely to experience overcrowding were first identified: the median refuge island at the main entrance and the turnstiles. The station performance at those critical points was then evaluated for different passenger volumes, with mainly pedestrian density (persons/m2) as an indicator. Results indicated a pedestrian capacity range for a typical BRT station and also quantified the effect of friction between pedestrians entering and leaving the station. Finally, a regression based on the simulation results was estimated and used to develop a predictive equation for crowding as a function of passenger volumes and direction. The results can help BRT planners better adapt their station designs to forecast passenger volumes and ensure that they provide an adequate level of service.

Using Fuzzy Clustering of User Perception to Define Levels of Service at Signalized Intersections

2003 ◽  
Vol 129 (6) ◽  
pp. 657-663 ◽  
Author(s):  
Fang Clara Fang ◽  
Lily Elefteriadou ◽  
Kelly Klaver Pecheux ◽  
Martin T. Pietrucha
Keyword(s):  
Fuzzy Clustering ◽  
Signalized Intersections ◽  
User Perception ◽  
Levels Of Service

An Unsupervised Hybrid Symbolic Fuzzy Clustering Approach for Efficient Sclera Segmentation

2021 ◽  
Vol 10 (1) ◽  
pp. 1-14
Author(s):  
B. S. Harish ◽  
M. S. Maheshan ◽  
C. K. Roopa ◽  
S. V. Aruna Kumar
Keyword(s):  
Fuzzy Clustering ◽  
Clustering Methods ◽  
Cluster Validity ◽  
Clustering Method ◽  
Cluster Validity Indices ◽  
Validity Indices ◽  
Fuzzy Clustering Methods ◽  
Clustering Approach ◽  
Representation Method ◽  
Segmentation Task

This article performs the sclera segmentation task by proposing a new hybrid symbolic fuzzy c-means (HSFCM) clustering method. Practically, though the data point exhibits some sort of similarity, unfortunately they are not undistinguishable and exhibit some sort of dissimilarity. Thus, to capture these disparities, the proposed work uses symbolic interval valued representation method. Further, to handle uncertainty and imprecision, the paper has proposed to use symbolic fuzzy clustering methods. To assess the performance of the proposed method, extensive experimentation is conducted on SSRBC2016 dataset. The proposed clustering method is compared with existing FCM, KFCM, RSKFCM method in terms of cluster validity indices and accuracy. The obtained outcomes demonstrated that the proposed method performed better compared to the contemporary methods.

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