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Title:

Probabilistic Neural Network and Adaptive Neuro Fuzzy Inference System Based Paratransit Service Quality Prediction and Attribute Ranking

Accession Number:

01623271

Record Type:

Component

Abstract:

Two different Artificial Neural Network (ANN) models are developed in this study to evaluate the service quality (SQ) of paratransit based on user stated preferences. The ANN models are developed by adopting two different ANN approaches, namely Probabilistic Neural Network (PNN) and Adaptive Neuro-Fuzzy Inference System (ANFIS)using a questionnaire survey dataset of 2008 paratransit users of Dhaka City, Bangladesh. The study results show that PNN produces better prediction than ANFIS. The research is further extended to include ranking of the SQ attributes according to their influences on the overall results from the developed models. Out of twenty two SQ attributes, ‘Ticketing system (Fare Collection)’, ‘Quality of Driver’, and ‘Security of passengers’ are found to be the top three attributes those have the most effect in the users’ decision making process. This study can aid city transportation officials and service providers in improving the most important attributes of paratransit, thereby increasing paratransit ridership.

Supplemental Notes:

This paper was sponsored by TRB committee AP060 Standing Committee on Paratransit.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-00259

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Ahmed, Irfan Uddin
Banik, Rajib
Hasnat, Md. Mehedi
Hadiuzzaman, Md
Qiu, Tony Z
Rahman, Farzana

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Subject Areas:

Planning and Forecasting; Public Transportation

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-00259

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 9:59AM