Publication Type
Conference Poster
Version
publishedVersion
Publication Date
10-2021
Abstract
We present an interactive probing tool to create, modify and analyze what-if scenarios for multivariate time series models. The solution is applied to freight trading, where analysts can carry out sensitivity analysis on freight rates by changing demand and supply-related econometric variables and observing their resultant effects on freight indexes. We utilize various visualization techniques to enable intuitive scenario creation, alteration, and comprehension of time series inputs and model predictions. Our tool proved to be useful to the industry practitioners, demonstrated by a case study where freight traders are given hypothetical market scenarios and successfully generated quantitative freight index projection with confidence
Keywords
What-if Analysis, Multivariate Time Series Prediction, Human-centered Computing, Freight Rate Analysis
Discipline
Numerical Analysis and Scientific Computing | Software Engineering | Transportation
Research Areas
Software and Cyber-Physical Systems
Publication
IEEE VIS 2021: Poster, Virtual Conference, October 24-29
First Page
1
Last Page
1
Publisher
IEEE
City or Country
Virtual Conference
Citation
XU, Haonan; LI, Haotian; and WANG, Yong.
Interactive probing of multivariate time series prediction models: A case of freight rate analysis. (2021). IEEE VIS 2021: Poster, Virtual Conference, October 24-29. 1-1.
Available at: https://ink.library.smu.edu.sg/sis_research/6843
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://virtual-staging.ieeevis.org/year/2021/poster_v-vis-posters-1038.html
Included in
Numerical Analysis and Scientific Computing Commons, Software Engineering Commons, Transportation Commons