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Record W4390102257 · doi:10.5206/mase/16369

Solution of fractional modified Kawahara equation: a semi-analytic approach

2023· article· en· W4390102257 on OpenAlexvenueno aff
Sagar R. Khirsariya, S. B. Rao, Jignesh P. Chauhan

Bibliographic record

VenueMathematics in Applied Sciences and Engineering · 2023
Typearticle
Languageen
FieldMathematics
TopicFractional Differential Equations Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsMathematicsResidualHomotopy perturbation methodPower seriesApplied mathematicsHomotopy analysis methodContext (archaeology)Partial differential equationSeries (stratigraphy)Mathematical analysisPerturbation (astronomy)HomotopyAlgorithmPhysicsPure mathematics

Abstract

fetched live from OpenAlex

The present study examines a semi-analytical method known as the Fractional Residual Power Series Method for obtaining solutions to the non-linear, time-fractional Kawahara and modified Kawahara equations. These equations are fifth-order, non-linear partial differential equations that arise in the context of shallow water waves. The analytical process and findings are compared with those obtained from the well-known Variational Iteration Method (VIM) and Homotopy Perturbation Method (HPM). The results obtained from the Fractional Residual Power Series Method are found to be more efficient, reliable, and easier to implement compared to other analytical and semi-analytical 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.133
GPT teacher head0.313
Teacher spread0.180 · 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 designTheoretical or conceptual
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

Citations15
Published2023
Admission routes1
Has abstractyes

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