Related Experiment Video
Updated: Jan 22, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Bus Travel Time Prediction Model Based on Profile Similarity
Teresa Cristóbal1, Gabino Padrón1, Alexis Quesada-Arencibia1
1Institute for Cybernetics, University of Las Palmas de Gran Canaria, Campus de Tafira, 35017 Las Palmas, Spain.
Abstract:
In road-based mass transit systems, travel time is a key factor in providing quality of service. This article proposes a method of predicting travel time for this type of transport system. This method estimates travel time by taking into account its historical behaviour, represented by historical profiles, and the current behaviour recorded on the public transport vehicle for which the prediction is to be made. The model uses the k-medoids clustering algorithm to obtain historical travel time profiles. A relevant feature of the model is that it does not require recent travel time data from other vehicles. For this reason, the proposed model may be used in intercity transport contexts in which service planning is carried out according to timetables. The proposed model has been tested with two real cases of intercity public transport routes and from the results obtained we may conclude that, in general, the average error of the predictions is around 13% compared to the observed travel time values.
Related Concept Videos
Travelling Waves
Water waves, sound waves, and seismic waves are some examples of mechanical waves. For water waves, the wave propagation medium is...
Bus Impedance Matrix
In the first circuit, all machine voltage sources are short-circuited, leaving only the prefault voltage source at the fault location. The positive-sequence bus impedance matrix can be determined by solving the nodal equations,...
Causes of Similarity-Dissimilarity Effect
Traveling Waves: Lossless Lines
Factors Influencing Attraction III: Similarity
Predicting Molecular Geometry

