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Record W2114371948 · doi:10.1109/tmech.2010.2043535

Axiomatic-Design-Theory-Based Approach to Modeling Linear High Order System Dynamics

2010· article· en· W2114371948 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAxiomatic designAxiomatic systemComputer scienceAxiomIndependence (probability theory)System dynamicsSet (abstract data type)Axiom independenceMathematical optimizationMathematicsArtificial intelligenceEngineeringProgramming language

Abstract

fetched live from OpenAlex

This paper presents a systematic approach to modeling linear high-order system dynamics for the purpose of control. The philosophy behind this approach is that system modeling can be made analogous to system design. In particular, functional requirements (in design) are analogous to dynamics (in modeling) of the system to be modeled and design parameters (in design) correspond to models (in modeling). With this philosophy, we assume that a model can be decomposed into a set of basic models. We then apply the axiomatic design theory (ADT) developed by Suh in the late 1980s, in particular independence axiom of ADT, to determine these basic models. Four experiments were conducted, and the results have shown that our approach is very promising, as opposed to the existing approaches, in terms of model accuracy and model development efficiency.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.657
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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