INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
ABSTRACT:
Passenger train delay significantly influences riders to choose rail transport as their mode choice. This paper proposes real-time passenger train delay prediction (PTDP) models using machine learning techniques. In this article, the impact on PTPD models using real-time with real-time-based data-frame structure (RT-DFS) and history-based data-frame structure (RWH-DFS) is investigated. The results show that PTDP models using MLP with RWH-DFS outperformed all other models. The influence of external variables such as historical delay profiles (HDPD), ridership and population, day of the week, geography and weather information on real-time PTPD models is further analyzed and discussed.
This system is very important for improving airport traffic efficiency to improve accuracy in predicting train arrival delay time. In our process, we need to take the input as a time series dataset. After that, machine learning algorithms like logistic regression and random forest should be implemented. Experimental results show that each algorithm has accuracy and error values. The model has good predictive accuracy and can track the trends of many delay indicators well.
Keywords:
RANDOM FOREST, LOGISTICS REGRESSION.
Cite Article:
"Data Analytics Approach for Train Time Table Performance Measure Using Automatic Train Supervision Data", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.f341-f346, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305559.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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