On-device research index

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

Trend · papers per month

count % of corpus

7 results for “echo-sounder buoys”

Tuna-AI: tuna biomass estimation with Machine Learning models trained on oceanography and echosounder FAD datastat.ML

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.

tuna biomass Machine Learning echo-sounder oceanography buoy

2021-09-14abs ↗pdf ↗

How do tuna schools associate to dFADs? A study using echo-sounder buoys to identify global patternsstat.ML

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.

tuna schools dFADs echo-sounder buoys Machine Learning temporal trends

2022-07-14abs ↗pdf ↗

Robust Marine Buoy Placement for Ship Detection Using Dropout K-Meanscs.LG

Marine buoys aid in the battle against Illegal, Unreported and Unregulated (IUU) fishing by detecting fishing vessels in their vicinity. Marine buoys, however, may be disrupted by natural causes and buoy vandalism. In this paper, we formulate marine buoy placement as a clustering problem, and propose dropout k-means an…

2020-01-02abs ↗pdf ↗

Dynamic Modeling and Adaptive Controlling in GPS-Intelligent Buoy (GIB) Systems Based on Neural-Fuzzy Networkseess.SY

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.

GPS-intelligent buoys neural-fuzzy networks dynamic modeling adaptive control backstepping

2020-04-03abs ↗pdf ↗

Gaussian processes at the Helm(holtz): A more fluid model for ocean currentsstat.ME

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.

Gaussian processes ocean currents Helmholtz decomposition divergence identification sparse data

2023-02-20abs ↗pdf ↗

Exceedance Probability Forecasting via Regression for Significant Wave Height Predictionstat.ML

New method predicts wave height exceedance probabilities.

problem Forecasting significant wave height to prevent coastal disasters.

method Point forecasting approach using cumulative distribution function.

result Proposed method outperforms existing approaches.

wave height exceedance probability ocean forecasting smart buoy binary classification

2022-06-20abs ↗pdf ↗

Off-the-shelf deep learning is not enough: parsimony, Bayes and causalityphysics.comp-ph

Deep learning excels in AI but struggles with causal physics.

problem Deep learning struggles with causal relationships in physical sciences.

method Combining Bayesian methods, physical constraints, and causal models.

result Deep learning can mislead in systems with unclear causal relationships.

deep learning materials science causality Bayesian methods physical constraints

2020-05-04abs ↗pdf ↗