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Reliability Analysis of Highway Network Communication System Based on the Fault Tree Analysis Method

2012· article· en· W2079439126 on OpenAlexaff
Xu Jia, Li Wei Zhu

Bibliographic record

VenueApplied Mechanics and Materials · 2012
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Computational Techniques and Applications
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsFault tree analysisReliability (semiconductor)Reliability engineeringFault (geology)EngineeringWork (physics)Function (biology)Tree (set theory)System modelComputer scienceSystems engineeringMechanical engineering

Abstract

fetched live from OpenAlex

After introduced the composition and function of Highway Network Communication System (HNCS), the HNCS model was established based on the fault tree analysis method. According to the provided impact assessment model, the influence of highway electromechanical system network reliability was analyzed, and subsequently the system reliability of HNCS was evaluated, This paper put forward the strategies to improving the network system reliability of highway electromechanical system, and providing the technical support for the maintenance work of highway network system electromechanical equipments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.279
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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