@inproceedings{e564f3c3d01a4f2b9c5138e96acfd4da,
title = "Capturing emergent behavior in multi-response systems through data trend mining",
abstract = "This paper presents a novel approach to capture emerging systems behavior involving multiple performance criteria. Due to the interactions that exist among systems, engineers may be faced with a multi-objective design space that current single response data mining models do not capture. We aim to address this challenge by proposing a Multi-Response Trend Mining algorithm that simultaneously predicts multiple performance objectives by identifying the time series behavior of the individual systems. The proposed approach is a departure from conventional data mining approaches that are often limited to evaluating single response variables in a given static data set. The resulting system level predictions will serve as performance targets for next generation systems design efforts. The Multi- Response Trend Mining model can then be integrated with multi-objective engineering models during the systems design and analysis phase so that engineering design solutions better reflect emerging system performance trends. A vehicle design data set from the UC Irvine Machine Learning Repository is used to validate the proposed methodology and highlight the need for multi-response predictive algorithms in systems design.",
author = "Tucker, {Conrad S.} and Kim, {Harrison M.}",
note = "Funding Information: The work presented in this paper is supported by Sandia National Labs, SURGE and the National Science Foundation under Award No. CMMI-0726934. Any opinions, findings and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of Sandia National Labs, SURGE or the National Science Foundation. The authors would like to acknowledge Yohannes Kifle for the programming aspects and software development of this work which can be found at (http://www.trendminingdesign.com/).; 13th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, MAO 2010 ; Conference date: 13-09-2010 Through 15-09-2010",
year = "2010",
doi = "10.2514/6.2010-9322",
language = "English (US)",
isbn = "9781600869549",
series = "13th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference 2010",
booktitle = "13th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference 2010",
}