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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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0111 · Jan 202019922001200920172026
7 results for buoy

The paper improves marine buoy placement to detect ships robustly against disruptions.

problem Detecting fishing vessels in the presence of natural and man-made disruptions.
method Formulated as a clustering problem, used dropout k-means and k-median to improve buoy placement robustness.
result Improved ship detection probability with dropout k-means compared to classic methods.

Paper develops a neural-fuzzy controller for GPS-intelligent buoys.

problem Optimally track dynamically positioned marine buoys with unknown parameters.
method Dynamic system modeling using neural-fuzzy networks with backstepping technique.
result The controller minimizes position errors and adjusts buoy positions accurately.

Tuna-AI uses ML to predict tuna biomass from oceanography and echo-sounder data.

problem Estimating tuna biomass from limited data sources.
method Developed a Machine Learning model using 3-day echo-sounder data and oceanographic data.
result Tuna-AI predicts tuna biomass with high accuracy using a 3-day window of data.

Study uses echo-sounder buoys to analyze tuna schools' association with dFADs globally.

problem Understanding temporal trends of tuna schools' association to drifting objects.
method Applied Machine Learning to examine binary and regression outputs of tuna schools' colonization and disaggregation times.
result Median colonization and disaggregation times varied by ocean, with Pacific having longest soak and colonization times.

Gaussian processes improved for ocean current reconstruction and divergence identification.

problem Reconstructing ocean currents from sparse buoy data.
method Proposed a Helmholtz decomposition-based approach to Gaussian processes for better physical modeling.
result Improved inference on ocean currents and divergence identification with minimal computational cost.