A scalable platform for big data analysis in public transport

Date

2021-01-01

Author

Uçak, Ege
Karagümüş, Elif
Şener, Cevat

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

92
views

0
downloads

Any life event or action can be seen as a potential source of data to analyze. By analyzing such data, we can gain insights into the facts. The situation is no different in public transport. Researchers working in the fields of transport and traffic have stated that such an analysis would be invaluable in designing urban transport and particularly in adapting to current changes. In this study, a scalable public transport analysis platform named Cermoni is developed using the Apache Beam programming model. It can analyze in near-real-time smart card and vehicle location data collected, classified as big data with its high production speed. The performance of the platform was tested on Google Cloud Dataflow service using real-world data gathered from Konya, one of the largest metropolitan cities in Turkey, and the results are discussed in detail.

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85111099714&origin=inward
https://hdl.handle.net/11511/91544

Journal

Concurrency and Computation: Practice and Experience

DOI

https://doi.org/10.1002/cpe.6534

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Vehicle detection on small scale data by generative data augmentation Kumdakcı, Hilmi; Temizel, Alptekin; Department of Modeling and Simulation (2021-2-03) Scarcity of training data is one of the prominent problems for deep neural networks,which commonly require high amounts of data to display their potential. Data aug-mentation techniques are frequently applied during the pre-training and training phasesof deep neural networks to overcome the problem of having insufficient data for train-ing. These techniques aim to increase a neural network’s generalization performanceon unseen data by increasing the number of training samples and provide a more rep-resenta...
Fuzzy classification models based on tanaka’s fuzzy linear regression approach and nonparametric improved fuzzy classifier functions Özer, Gizem; Köksal, Gülser; Department of Industrial Engineering (2009) In some classification problems where human judgments, qualitative and imprecise data exist, uncertainty comes from fuzziness rather than randomness. Limited number of fuzzy classification approaches is available for use for these classification problems to capture the effect of fuzzy uncertainty imbedded in data. The scope of this study mainly comprises two parts: new fuzzy classification approaches based on Tanaka’s Fuzzy Linear Regression (FLR) approach, and an improvement of an existing one, Improved Fu...
An inquiry on Wittgenstein's conception of meaning Erşahin, Direnç; Turan, Şeref Halil; Department of Philosophy (2007) This study aims at investigating Wittgenstein’s conception of meaning. In this sense, philosopher’s early and later periods will be examined. Key notions of Wittgenstein’s philosophy of language, picture theory of meaning, language-game, rule following, Private Language Argument and his assertion that ‘meaning is use’ will be analyzed. Out of this analysis, Wittgenstein’s answer to the following basic question will be sought: How is meaning derived in a language? The outcome of this query will be comparativ...
Impact of Rescaling Approaches in Simple Fusion of Soil Moisture Products Afshar, Mahdı Hesamı ; Yılmaz, Mustafa Tuğrul (American Geophysical Union (AGU), 2019-09-10) In this study, the impact of various rescaling approaches in the framework of data fusion is explored. Four different soil moisture products (Advanced Scatterometer; Advanced Microwave Scanning Radiometer for EOS, AMSR-E; Antecedent Precipitation Index; and Global Land Data Assimilation System-NOAH) are fused. The systematic differences between products are removed before the fusion utilizing various rescaling approaches focusing on different methods (regression, variance/cumulative distribution function (C...
Possibilistic interpretation of mistuning in bladed disks by fuzzy algebra Karataş, Hamit Çağlar; Özgüven, Hasan Nevzat; Ciğeroğlu, Ender; Department of Mechanical Engineering (2012) This study aims to define the possibilistic interpretation of mistuning and examine the way of determining the worst case situations and assessing reliability value to that case by using possibilistic methods. Furthermore, in this study, benefits of using possibilistic interpretation of mistuning in comparison to probabilistic interpretation of mistuning are investigated. For the possibilistic analysis of mistuned structures, uncertain mistuning parameters are modeled as fuzzy variables possessing possibili...

Citation Formats

E. Uçak, E. Karagümüş, and C. Şener, “A scalable platform for big data analysis in public transport,” Concurrency and Computation: Practice and Experience, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85111099714&origin=inward.