In the last decades, there has been substantial development in modeling techniques of travel demand estimation. Most of the techniques concerning the construction and the calibration of these models were developed in industrialized countries of the world. In India, the construction and calibration of intercity travel demand follow mostly either the extrapolation of historical data, such as growth rates, or the re-calibration of models initially formulated and estimated for scenarios in industrialized countries. The objective of the proposed work is to perform time series analysis on historical data of railway passengers. In this paper, we apply time series decomposition model on railway data set which analyze time series components separately.
Railway passenger forecasting using time series decomposition model
2017-04-01
274949 byte
Conference paper
Electronic Resource
English
Railway passenger demand forecasting
IuD Bahn | 1998
|Short-Term Passenger Demand Forecasting Using Univariate Time Series Theory
DOAJ | 2013
|Forecasting railway freight and passenger transport in Hungary
Tema Archive | 1997
|