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Record W2376589217

Research on Anti-ship Missiles Application based on Simulation

2005· article· en· W2376589217 on OpenAlexaboutno aff
Sun Yong-kan

Bibliographic record

VenueFire Control and Command Control · 2005
Typearticle
Languageen
FieldEngineering
TopicMilitary Defense Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMissileScheme (mathematics)SoftwareDelphiSimulation softwareKey (lock)EngineeringSystems engineeringBattleSimulationComputer scienceAerospace engineeringComputer securityOperating system
DOInot available

Abstract

fetched live from OpenAlex

Anti-ship missiles application research is the key for warships arms to form battle effectiveness.A simulation platform of anti-ship missiles application was built,which based on STAGE,the combat simulation software of Canada ENGENUITY Technologies Inc and Delphi,the integrated development software of Borland Software Corp.It introduced the platform's simulation method to integrate analytic simulation with synthetic simulation,as well as its simulation framework.A kind of anti-ship missile was modeled and simulated on this platform.A technical bug of the missile's hunting scheme is found out.After analyzed the missile's optimizing scheme and updating scheme,the simulation platform proves to be useful.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.270
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2005
Admission routes1
Has abstractyes

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