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May 24, 2026Annals of Operations ResearchOpen Access

Enhancing a multilayer perceptron model for multi-state network reliability evaluation via an arc-wise architecture

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Authors

TNThi-Phuong NguyenCYCheng-Ta YehCFChien-Chih Fang

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Overview

Randomized trial evaluates a new multilayer perceptron model for reliability in multi-state networks, suggesting improved accuracy and efficiency.

Key Points

  • The aim is to improve the reliability estimation of multi-state networks using an enhanced multilayer perceptron model.
  • Developed an arc-wise architecture where each arc is represented by a dedicated subnetwork.
  • Incorporated system-level requirements into the MLP's input layer.
  • Validated the approach through numerical experiments combined with Bayesian optimization for hyperparameter tuning.
  • Achieved high estimation accuracy in reliability analysis.
  • Demonstrated enhanced efficiency in modeling large-scale multi-state networks.

Cite This Study

Nguyen et al. (2026) studied this question.

synapsesocial.com/papers/6a12959d48a0ea1665671b3dhttps://doi.org/10.1007/s10479-026-07283-x
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