A literature review of Artificial Intelligence applications in railway systems

Tang, Ruifan; Donato, Lorenzo De; Bešinović, Nikola; Flammini, Francesco; Goverde, Rob M.P.; Lin, Zhiyuan; Liu, Ronghui; Tang, Tianli; Vittorini, Valeria; Wang, Ziyulong

doi:10.1016/j.trc.2022.103679

Cited by 127 publications

(35 citation statements)

References 129 publications

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“…CT provides better sensitivity than X-ray and RT-PCR [6]. Due to the rapid growth of essential data and the need to analyse the relationships and hierarchy between data, machine learning and data mining techniques are researched in the health system to provide efficiency in prevention, diagnosis and treatment [7].…”

Section: Related Workmentioning

confidence: 99%

Improving COVID 19 Detection based on a hybrid data mining approach

Goda¹

2022

IJCI. International Journal of Computers and Information

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The worldwide spread of coronavirus disease (COVID-19) has become a threatening risk for global public health. Currently, doctors resort to PCR analysis, however, it suffers from low accuracy problems. On the other hand, Convolutional neural network (CNN) and despite its high accuracy incorrect classification, it takes a long time to train data, in addition it requires large training dataset. In this paper, we propose a hybrid approach for COVID-19 detection and diagnosis. Our contribution consists of two phases to provide high detection accuracy. In the first phase, we propose a hybrid features-fusion phase that works by fusing four common features extracted from medical image, Row pixel intensity, Colour histogram, Harlick texture and Threshold. Each single classifier is fed with these four features and yielded a 4 different predictions for each feature. A well-known voting technique is then applied to provide final predication result for each classifier. Secondly, the ensemble stacking technique is employed to fuse predication of each classifier, which significantly improves final detection accuracy. The proposed approach has been quantitatively evaluated on a public dataset of 5000 CT-images. The proposed approach yields accuracy of 99.3% and overcome traditional approaches such as KNN (K-nearest neighbours) that yields 92%, and SVM (Support vector machines) that yields 92% comparable computational time that is approximately 4.9 minutes.

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Section: Related Workmentioning

confidence: 99%

Improving COVID 19 Detection based on a hybrid data mining approach

Goda¹

2022

IJCI. International Journal of Computers and Information

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“…Previous literature reviews have predominantly focused on the academic landscape, providing insights into specific domains. For instance, Tang et al. (2022) provide a summary of AI research connected to rail transport through 139 scientific papers published in the past 10 years.…”

Section: Introductionmentioning

confidence: 99%

Current state and predicted technological trends in global railway intelligent digital transformation

Li,

Xue,

Shao

et al. 2023

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PurposeIn recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.Design/methodology/approachThis paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.FindingsDigital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.Originality/valueThe results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

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“…Some researchers highlight the problem of a bad influence of railway lines on the surrounding area and for residents [ 35 , 36 ]. A literature review of applications of artificial intelligence to rail systems is described in [ 37 ]. In medium-sized cities (up to one million residents in a metropolitan area), the basis of public transportation is a tramway or tramway in combination with a suburban railroad.…”

Section: Introductionmentioning

confidence: 99%

Modified Ant Colony Optimization as a Means for Evaluating the Variants of the City Railway Underground Section

Korzeń

Kruszyna

2023

IJERPH

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The railway is one of the most energy-efficient modes of transport, helping to enhance the environment and public health in cities and agglomerations. In this paper, the authors raise the issue of the construction of an underground railway route in Wrocław (Poland) to allow the organization of the suburban rail system in the agglomeration. There are many concepts for the construction of this route, but so far none has been realized. Therefore, it is important to design the route properly. Here, five options for this tunnel are considered and evaluated. To make such an evaluation, the authors construct a modified ant colony optimization algorithm (ACO). The “classic” algorithm considers the determination of the shortest route. The modification of the algorithm will allow a more accurate analysis of the issue, taking into account more parameters than just the length of the route. These are the location of traffic generators in the city center, the number of inhabitants neighboring the stations, and the number of tram or bus lines integrated with the railway. The presented method and exemplary case study should allow for the evaluation, introduction, or development of the city railway.

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A literature review of Artificial Intelligence applications in railway systems

Cited by 127 publications

References 129 publications

Improving COVID 19 Detection based on a hybrid data mining approach

Improving COVID 19 Detection based on a hybrid data mining approach

Current state and predicted technological trends in global railway intelligent digital transformation

Modified Ant Colony Optimization as a Means for Evaluating the Variants of the City Railway Underground Section

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