An Expert System with Layered Evolution-Based Feature Extraction for Epidemic Monitoring

Authors

  • Cheng-Yi Wang Center for Continuing Education, National Tsing Hua University, Hsinchu, Taiwan | College of Management, Chung Hua University, Hsinchu, Taiwan
  • Chien-Ta Ho Graduate Institute of Technology Management, National Chung Hsing University, Taichung, Taiwan
  • Yi-Siang Chen R&D Management, Wuyun Information Corporation, Taichung, Taiwan
  • Yan-Kwang Chen Department of Distribution Management, National Taichung University of Science and Technology, Taichung, Taiwan

DOI:

https://doi.org/10.23055/ijietap.2026.33.2.11331

Keywords:

Expert System; Feature Extraction; Artificial Intelligence; Epidemic Monitoring; Public Health.

Abstract

Enhancing epidemic monitoring capabilities to support policymaking has become a global health priority. This study proposes a layered evolution-based expert system that integrates feature extraction, feature importance analysis, and robustness-oriented design for epidemic trend monitoring. The proposed framework combines genetic algorithm (GA)-based evolutionary mechanisms with Taguchi method-based optimal operating condition design to enhance analytical stability under varying configurations. Using publicly available COVID-19 data from Japan, the proposed system monitors epidemic dynamics across four mortality levels while simultaneously identifying representative features and estimating their relative importance. The results demonstrate that the system reduces the feature set by approximately 27% while maintaining stable predictive performance under more granular severity definitions. Robustness is further evaluated through statistical validation under varying dataset compositions and scales. Overall, the proposed expert system provides an interpretable and robust framework for epidemic trend monitoring that complements existing prediction-oriented approaches and may support informed public health decision processes through feature-level insights.

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Published

2026-04-09

How to Cite

Wang, C.-Y., Ho, C.-T., Chen, Y.-S., & Chen, Y.-K. (2026). An Expert System with Layered Evolution-Based Feature Extraction for Epidemic Monitoring. International Journal of Industrial Engineering: Theory, Applications and Practice, 33(2). https://doi.org/10.23055/ijietap.2026.33.2.11331

Issue

Vol. 33 No. 2 (2026)

Section

Information System and Technology

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