About this document
Predicting Bike Trip Duration and Distance by amirabourechak is a document available to read on EtoBox.
This research article presents a novel approach to predicting trip duration and distance in bike-sharing systems (BSS) using dynamic time warping (DTW) for clustering dataset instances. The study demonstrates that training predictive models on clustered subsets of data improves accuracy significantly compared to using the entire dataset. The proposed method was evaluated on two real datasets, achieving average accuracy improvements of 30% for trip duration and 42% for trip distance predictions.
- Author
- amirabourechak
- Language
- EN