ArticleScientific reports2025
A new method for assessing the health status of aerospace equipment based on a belief rule base with balanced accuracy and complexity.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The health status of aerospace equipment directly affects the operational capability of the entire system. Belief rule base (BRB) is an effective method for assessing health status that combines expert knowledge and historical data. However, in the actual assessment, the data provided by experts only form the basic framework of the model. Therefore, the BRB model with joint optimization of structure and parameters (BRB-SPO) is proposed to achieve a balance between the model's accuracy and complexity. First, to balance complexity and accuracy of the model, parameter structure backward stepwise selection method (BSS) and full factorial design (FFD) are introduced. BSS constructs the optimal parameter set, while FFD determines the best parameter values for the model. Subsequently, the constructed model is deduced using the evidential reasoning (ER) calculation procedure, the other parameters are optimized using the projection covariance matrix adaptive evolution strategy (P-CMA-ES). Finally, the practicality of the proposed method is validated through two examples.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.