MétaCan
Menu
Back to cohort

Control and Function Projective Synchronization of 3D Chaotic System

2024· article· en· W4404762458 on OpenAlexvenueno aff
M. M. El‐Dessoky, Ebraheem Alzahrani, Z. A. Abdulmannan

Bibliographic record

VenueInternational Journal of Analysis and Applications · 2024
Typearticle
Languageen
FieldComputer Science
TopicNeural Networks and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMathematicsProjective testChaoticSynchronization (alternating current)Function (biology)Synchronization of chaosControl (management)Chaotic systemsControl theory (sociology)Pure mathematicsComputer scienceTopology (electrical circuits)Artificial intelligenceCombinatorics

Abstract

fetched live from OpenAlex

In this paper, we study a linear feedback control to dampen the chaotic behavior of a 3D dynamic system. Based on the Routh-Hurwitz criterion, the conditions are determined to achieve control. Furthermore, function projective synchronization (FPS) between two identical 3D chaotic systems is demonstrated. The proof of asymptotic stability of solutions for the error dynamical system depends on the negative eigenvalues of the system. Additionally, numerical simulations are utilized to demonstrate the impact and effectiveness of the proposed methods.

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 score0.002
Threshold uncertainty score0.004

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 science0.0000.001
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 head0.005
GPT teacher head0.245
Teacher spread0.239 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Analysis and ApplicationsSame topicNeural Networks and ApplicationsFrench-language works237,207