Real-time data stream learning for emergency decision-making under uncertainty

Kun Wang, Li Xiong and Rudan Xue

Physica A: Statistical Mechanics and its Applications, 2024, vol. 633, issue C

Abstract: As one factor resulting in health emergency, climate change has received high attention in recent years. Real-time identifying and tracking the potential climate-related risk becomes more challenging due to the changeable and evolving data under uncertainty. To enhance risk early warning and decision-making, this paper proposes a self-adaptive machine learning framework based on real-time data stream learning, called C-SA-Stacking, for risk prediction. First, a stacking-based ensemble model for data stream learning is built with a meta-model embedded, which can self-update selectively and dynamically. Second, an online learning scheme is added to this framework for real-time adaptation. Finally, a mapping of correlations between data streams is constructed to further enhance the learning performance. By testing the framework on six synthetic datasets and six real-world datasets with different risk change scenarios and conducting comparative experimental analysis, the experimental results show that the prediction error is reduced as respected, indicating the effectiveness and real-time of the proposed framework for risk prediction under uncertainty. The results discussion reflects the framework can be applied to real-world scenarios to help identify and track the risk of climate change-caused health emergencies for decision-making.

Keywords: Data stream; Machine learning; Decision making; Emergency (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437123009846
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:633:y:2024:i:c:s0378437123009846

DOI: 10.1016/j.physa.2023.129429

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().