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Record W2120816053 · doi:10.1142/s0218127411030003

BIFURCATION CONTROL FOR A CLASS OF LORENZ-LIKE SYSTEMS

2011· article· en· W2120816053 on OpenAlexafffund
Pei Yu, Jinhu Lü

Bibliographic record

VenueInternational Journal of Bifurcation and Chaos · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicChaos control and synchronization
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsLorenz systemControl theory (sociology)Biological applications of bifurcation theoryMathematicsNonlinear systemChaoticClass (philosophy)Limit (mathematics)Stability (learning theory)BifurcationChenHopf bifurcationSimple (philosophy)Applied mathematicsSaddle-node bifurcationLimit cycleControl (management)Computer scienceMathematical analysisAttractorPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, a control method developed earlier is employed to consider controlling bifurcations in a class of Lorenz-like systems. Particular attention is focused on Hopf bifurcation control via linear and nonlinear stability analyses. The Lorenz system, Chen system and Lü system are studied in detail. Simple feedback controls are designed for controlling the stability of equilibrium solutions, limit cycles and chaotic motions. All formulas are derived in general forms including the system parameters. Computer simulation results are presented to confirm the analytical predictions.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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

Citations16
Published2011
Admission routes2
Has abstractyes

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