Interactive probing of multivariate time series prediction models: A case of freight rate analysis
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 o...
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sg-smu-ink.sis_research-78462022-05-09T07:17:40Z Interactive probing of multivariate time series prediction models: A case of freight rate analysis XU, Haonan LI, Haotian WANG, Yong 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 2021-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6843 https://ink.library.smu.edu.sg/context/sis_research/article/7846/viewcontent/21_IEEEVIS_poster_probing.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University What-if Analysis Multivariate Time Series Prediction Human-centered Computing Freight Rate Analysis Numerical Analysis and Scientific Computing Software Engineering Transportation |
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What-if Analysis Multivariate Time Series Prediction Human-centered Computing Freight Rate Analysis Numerical Analysis and Scientific Computing Software Engineering Transportation XU, Haonan LI, Haotian WANG, Yong Interactive probing of multivariate time series prediction models: A case of freight rate analysis |
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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 |
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text |
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XU, Haonan LI, Haotian WANG, Yong |
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XU, Haonan LI, Haotian WANG, Yong |
author_sort |
XU, Haonan |
title |
Interactive probing of multivariate time series prediction models: A case of freight rate analysis |
title_short |
Interactive probing of multivariate time series prediction models: A case of freight rate analysis |
title_full |
Interactive probing of multivariate time series prediction models: A case of freight rate analysis |
title_fullStr |
Interactive probing of multivariate time series prediction models: A case of freight rate analysis |
title_full_unstemmed |
Interactive probing of multivariate time series prediction models: A case of freight rate analysis |
title_sort |
interactive probing of multivariate time series prediction models: a case of freight rate analysis |
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Institutional Knowledge at Singapore Management University |
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2021 |
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https://ink.library.smu.edu.sg/sis_research/6843 https://ink.library.smu.edu.sg/context/sis_research/article/7846/viewcontent/21_IEEEVIS_poster_probing.pdf |
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