Combining Spatial and Temporal Aspects of Prediction Problems to Improve Prediction Performance
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2806-2806.
Abstract
Quantitative prediction problems involving both spatial and temporal components have appeared prominently in several disparate research areas including finance, supply chain management, and civil engineering. Unfortunately, either the spatial or temporal aspect tends to dominate the other in many prediction formulations. We briefly examine the underlying formulations used in spatial and temporal prediction. Then, we outline a method that combines these approaches and improves prediction results in high-dimensional economic domains by integrating multivariate and time series techniques which require minimal tuning but achieve superior performance compared to previous methods. We present preliminary results in the context of the Trading Agent Competition for Supply Chain Management.
@inproceedings{ijcai2011p475,
title = {Combining Spatial and Temporal Aspects of Prediction Problems to Improve Prediction Performance},
author = {Groves, William},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {2806--2806},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-475},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-475},
}
TY - CPAPER TI - Combining Spatial and Temporal Aspects of Prediction Problems to Improve Prediction Performance AU - Groves, William T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 2806 EP - 2806 DO - 10.5591/978-1-57735-516-8/IJCAI11-475 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-475 ER -Copied
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