Prediction of passenger flow for north central railway region through ANN. Issue 1 (June 2021)

• Record Type: Journal Article
• Authors: Singh, Anoop Pratap; Tripathi, Ajay; Dwivedi, Ravi Kumar; Garg, Anurag; Kumar, Rajan
• Is Part Of: IOP conference series. Volume 1136:Issue 1(2021)
• Publication Date: 2021-06
• Subjects: Passenger flow prediction -- back propagation(BP) -- neural network -- data analysis; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1136/1/012023
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: A new method of prediction method is described in this paper. The passenger rate for the north central railway (NCR) region is estimated by using artificial neural networks (ANN). An ANN model is developed here that can logically estimate passenger flow rates. Which helps the decision makers to make the strategies according to the falling population. In this analysis data from the North Central Railway region from January 2009 to December 2015 have been taken, data such as passenger revenue, months and years, festival seasons and passenger numbers. When predicting passenger flows for the months of January and February 2016, an error of less than 2.9% is found. Therefore, it's concluded that an ANN prediction method is applied in passenger flow prediction in railways.