dc.contributor.author | Sharma, Haresh Kumar | |
dc.contributor.author | Majumder, Saibal | |
dc.contributor.author | Biswas, Arindam | |
dc.contributor.author | Prentkovskis, Olegas | |
dc.contributor.author | Kar, Samarjit | |
dc.contributor.author | Skačkauskas, Paulius | |
dc.date.accessioned | 2023-09-18T16:19:04Z | |
dc.date.available | 2023-09-18T16:19:04Z | |
dc.date.issued | 2022 | |
dc.identifier.issn | 0197-6729 | |
dc.identifier.other | (crossref_id)138524114 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/113133 | |
dc.description.abstract | The Indian Railways Reservation System (IRRS) is one of the world’s busiest reservation systems of railway tickets. Recently, the COVID-19 pandemic situation has severely impacted the Indian Railway’s (IR) transportation, which eventually has enforced the IR to alter the passenger reservation system. This research attempts to evaluate and analyse the factors that modify the IRRS. In this research, a rough set-based Data Mining Scaffolding (DMS) has been proposed. Here, the relevant preferential information related to the IRRS is managed by introducing a multi-criteria decision-making (MCDM), where a decision-maker (DM) can make a decision based on several decision rules. The effectiveness of the proposed DMS is explained by gathering realistic data of 26 trains, which run between railway stations of two metro cities of India during the COVID-19 pandemic period. | eng |
dc.format | PDF | |
dc.format.extent | p. 1-10 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.relation.isreferencedby | Scopus | |
dc.title | A study on decision-making of the Indian Railways Reservation System during COVID-19 | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.references | 28 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Shree Guru Gobind Singh Tricentenary University | |
dc.contributor.institution | NSHM Knowledge Campus | |
dc.contributor.institution | Kazi Nazrul University (Public University) | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.institution | National Institute of Technology, Durgapur | |
dc.contributor.faculty | Transporto inžinerijos fakultetas / Faculty of Transport Engineering | |
dc.subject.researchfield | T 003 - Transporto inžinerija / Transport engineering | |
dc.subject.vgtuprioritizedfields | TD05 - Miesto judumas / Urban mobility | |
dc.subject.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
dc.subject.en | multiple criteria decision-making | |
dc.subject.en | rough set theory | |
dc.subject.en | COVID-19 | |
dc.subject.en | data mining | |
dc.subject.en | railway reservation system | |
dcterms.sourcetitle | Journal of advanced transportation | |
dc.description.volume | vol. 2022 | |
dc.publisher.name | Wiley | |
dc.publisher.city | London | |
dc.identifier.doi | 138524114 | |
dc.identifier.doi | 000831935800001 | |
dc.identifier.doi | 10.1155/2022/7685375 | |
dc.identifier.elaba | 135160756 | |