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Record W4390713557 · doi:10.23977/jeeem.2023.060515

Multibeam bathymetry optimization problem based on geometric modeling and simulated annealing

2023· article· en· W4390713557 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Electrotechnology Electrical Engineering and Management · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing and LiDAR Applications
Canadian institutionsnot available
Fundersnot available
KeywordsBathymetrySimulated annealingDepth soundingSeafloor spreadingEcho soundingGeologySeabedGeodesyUnderwaterGeometryRemote sensingAlgorithmComputer scienceMathematicsGeophysicsOceanography

Abstract

fetched live from OpenAlex

Echo sounding is a technique commonly used in marine bathymetry to measure the depth and topography of water bodies. This paper combs the development process of echo sounding technology, briefly describes the principle of multibeam bathymetry, and its application in ocean bathymetry and water conservancy engineering. In order to get the optimized scheme of the survey line in the rectangular sea area, this paper firstly draws a spatial 3D scatter plot using the attached data to observe the general shape of the seabed surface. Then, polynomial fitting is utilized to fit the surface to all points to obtain the surface equation. From the scatter plot, it can be seen that the seafloor slope is relatively gentle, and if the formula for the coverage width when the seafloor slope is horizontal can be used for calculation, the model will be greatly simplified. The programming in this paper verifies the reasonableness of the conjecture, so the simplified formula can be used for subsequent calculations. In order to determine the number of survey lines, a simulated annealing algorithm was used, and finally, we designed 31 parallel survey lines in the north-south direction, with a total length of 155 nautical miles, and the omitted sea area accounted for 1.71% of the total area to be surveyed, and in the overlapping area, the overlap rate of the part of the overlap rate of more than 20% had a total length of zero.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.694
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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