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Passenger Train Delay Classification

Passenger Train Delay Classification
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Author(s): Masoud Yaghini (Iran University of Science and Technology, Iran), Maryam Setayesh Sanai (Iran University of Science and Technology, Iran)and Hossein Amin Sadrabady (Research and Training Center of Iranian Railways, Iran)
Copyright: 2015
Pages: 10
Source title: Transportation Systems and Engineering: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-8473-7.ch014

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Abstract

One of the most popular data mining areas, which estimate future trends of data, is classification. This research is dedicated to predict Iranian passenger train delay with high accuracy over Iranian railway network. A hybrid method based on neuro-fuzzy inference system and Two-step clustering is used for this purpose. The results indicate that the hybrid method is superior over the other common classification methods. The result can be used by train dispatcher to accurate schedule trains to diminish train delay average.

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