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December 10, 2025International Journal of Pattern Recognition and Artificial Intelligence

A Dynamic System Structure Modeling and Evolution Identification Method Based on Multi-Source Signal Fusion

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Authors

YZYulong ZhangUniversity of South ChinaBJBo JinChengdu Medical CollegeYZYaqing ZhangShanghai Jiao Tong University

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Implication

The FUSE-ID framework identifies structural changes in systems, using time series data to enhance fault diagnosis and adaptive control.

Key Points

  • This work aims to develop a method for identifying and modeling structural evolution in dynamic systems based on multi-source signals.
  • Developed the FUSE-ID framework for dynamic systems modeling.
  • Utilized multi-source signal integration, including time series and sensor data.
  • Implemented an adaptive fusion module to capture inter-source dependencies.
  • Achieved high modeling accuracy and effective evolution tracking.
  • Demonstrated robustness to noisy observations in both synthetic and real-world datasets.
  • Enhanced capabilities for fault diagnosis and adaptive control in complex environments.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/69401b262d562116f28f7a37https://doi.org/10.1142/s0218001425550195
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