@inproceedings{59d6fc2d8fe843859362234859dc3681,
title = "Learning partial-value variable relations for system modeling",
abstract = "An important part of system modeling involves establishing relations of system variables. Data collected from a system reflects relations of system variables and thus allows us to learn variable relations from system data. Existing machine learning and data mining techniques focus on learning variable relations that hold for all values of variables. However, different variable relations may exist for different ranges of variable values, or a variable relation holds only for certain ranges of variable values but not for full ranges of variable values. This paper presents the use of a new algorithm, called Partial-Value Association Discovery (PVAD), to learn partial-value variable relations for energy consumption system modeling and engineering retention.",
keywords = "data mining, machine learning, system modeling",
author = "Nong Ye and Fok, {Ting Yan} and Xin Wang and James Collofello and Nancy Dickson",
note = "Funding Information: ACKNOWLEDGMENT This material is based upon work supported by the National Science Foundation under Award Number 1561496. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The author would like to Dr. Oswald Chong for providing the ASU energy consumption data. Publisher Copyright: {\textcopyright} 2018 IEEE.; 4th International Conference on Control, Automation and Robotics, ICCAR 2018 ; Conference date: 20-04-2018 Through 23-04-2018",
year = "2018",
month = jun,
day = "13",
doi = "10.1109/ICCAR.2018.8384702",
language = "English (US)",
series = "Proceedings - 2018 4th International Conference on Control, Automation and Robotics, ICCAR 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "368--372",
booktitle = "Proceedings - 2018 4th International Conference on Control, Automation and Robotics, ICCAR 2018",
}