PREDICTING THE ARRIVAL OF EMERGENT PATIENT BY AFFINITY SET

Yuh-Wen Chen, Moussa Larbani, Chao-Wen Chen

2008

Abstract

Predicting the time series of emergent patient arrival is valuable in monitoring/tracking the daily patient flow because these efforts keep doctors alarmed in advance. A prediction problem of the time series generated by actual arrival of emergent patient is considered here. Traditionally, such a problem is analyzed by moving average method, regression method, exponential smoothing method or some existed evolutionary methods. However, we propose a new affinity model to accomplish this goal. Our data of time series is actually recorded from hour to hour (hourly data) for three days: the data of the first two days are used to generate/train prediction model; after that, the data of the final/third day is used to test our prediction results. Two types of model: affinity model and neural network model are used for comparing their performances. Interestingly, the affinity model performs better prediction results. This hints there could be a special pattern within the time series generated by actual arrival of emergent patient.

References

  1. Abdel-Aal, R. E., & Al-Garni, A. Z., 1997. Forecasting monthly electric energy consumption in eastern Saudi Arabia using univariate time series analysis. Energy, Vol. 22, pp. 1059-1069.
  2. Agrawal R. and Srikant.R., 1995. Mining sequential patterns. In P. S. Yu and A. S. P. Chen, editors, Proceedings of the 11th International Conference on Data Engineering (ICDE'95), pp. 3-14, IEEE Press.
  3. TeleTracking, http://www.teletracking.com/ , visited in 2006.
  4. Kim, K. J., & Han, I., 2000. Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index. Expert Systems with Application, Vol. 19, pp. 125-132.
  5. Kimoto, T., and Asakawa, K., 1990. Stock market prediction system with modular neural network. Proceeding of IEEE International Joint Conference on Neural Network , pp. 1-6.
  6. Larbani, M. and Chen, Y. (2006). Affinity set and its applications. In Proceeding of the International Workshop on Multiple Criteria Decision Making, Apr. 14-18, 2007, Poland. Publisher of The Karol Adamiecki University of Economics in Katowice.
  7. Yu, P. L., 1985. Multiple Criteria Decision Making: Concepts, Techniques and Extensions. Plenum, New York.
Download


Paper Citation


in Harvard Style

Chen Y., Larbani M. and Chen C. (2008). PREDICTING THE ARRIVAL OF EMERGENT PATIENT BY AFFINITY SET . In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 4: CIAS, (ICEIS 2008) ISBN 978-989-8111-39-5, pages 273-277. DOI: 10.5220/0001723402730277


in Bibtex Style

@conference{cias08,
author={Yuh-Wen Chen and Moussa Larbani and Chao-Wen Chen},
title={PREDICTING THE ARRIVAL OF EMERGENT PATIENT BY AFFINITY SET},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 4: CIAS, (ICEIS 2008)},
year={2008},
pages={273-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001723402730277},
isbn={978-989-8111-39-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 4: CIAS, (ICEIS 2008)
TI - PREDICTING THE ARRIVAL OF EMERGENT PATIENT BY AFFINITY SET
SN - 978-989-8111-39-5
AU - Chen Y.
AU - Larbani M.
AU - Chen C.
PY - 2008
SP - 273
EP - 277
DO - 10.5220/0001723402730277