We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Forecasting the Passenger Volume of Taiwan High Speed Rail by Amensalistic Lotka-Volterra Model.
- Authors
Shih-Ching Lo
- Abstract
Forecasting passenger volume is crucial for transportation systems to effectively plan operations, determine ticket types, and set fare levels. To achieve this, a proposed aggregative model utilizes historical data from Taiwan's highspeed rail (HSR) passenger volume. The goal is to forecast passenger numbers without resorting to costly questionnaire surveys typically associated with discrete choice models. Instead, the study employs an amensalistic Lotka-Volterra model, integrating socio-economic variables such as gross domestic product (GDP), average income, average consumption, and population. Upon analyzing the results, it was discovered that utilizing average income as the sole socio-economic factor led to the most accurate forecasting of HSR passenger volume. This conclusion was drawn based on a mean absolute percentage error (MAPE) of approximately 5%, indicating a high level of forecasting accuracy. Furthermore, the coefficients of the model were interpreted consistently with general observations.
- Subjects
TAIWAN; HIGH speed trains; SOCIOECONOMIC factors; GROSS domestic product; PASSENGERS; INCOME; DISCRETE choice models
- Publication
IAENG International Journal of Applied Mathematics, 2024, Vol 54, Issue 7, p1427
- ISSN
1992-9978
- Publication type
Article