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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.

168,657 papers · 148 categories

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0111 · Nov 201019922001200920172026
17 results for rangeland biomass

Model predicts one-year NDVI for Four Corners region.

problem Long-term forecasting of vegetation conditions using climate attributes.
method Two-phase machine learning model using historical climate data.
result Open-source tools outperform alternative methods for NDVI forecasts.

Robotic weed control has seen increased research of late with its potential for boosting productivity in agriculture. Majority of works focus on developing robotics for croplands, ignoring the weed management problems facing rangeland stock farmers. Perhaps the greatest obstacle to widespread uptake of robotic weed con…

2018-10-09abs ↗pdf ↗

Method improves microbial biomass yield estimation from noisy data.

problem Estimating microbial biomass yields from noisy cell counts and substrate measurements.
method Probabilistic macrochemical modeling to relax cell weight assumptions and improve robustness.
result Model provides accurate uncertainty estimates of key parameters.

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 satellite and lidar data to map forest height and biomass in France.

problem Mapping forest resources and carbon in large areas.
method Machine learning approach using Sentinel-1, Sentinel-2, ALOS-2, and GEDI Lidar data.
result High-resolution maps of forest height and biomass produced with good accuracy.

New methods for predicting compositional data using conformal prediction.

problem No well-established methods for constructing valid prediction sets in compositional data.
method Investigated three conformal prediction-based approaches for Dirichlet regression models.
result HDR approximation approach is robust in terms of coverage, while grid discretization reduces overcoverage.

As most natural resources, fisheries are affected by random disturbances. The evolution of such resources may be modelled by a succession of deterministic process and random perturbations on biomass and/or growth rate at random times. We analyze the impact of the characteristics of the perturbations on the management o…

2019-09-04abs ↗pdf ↗

Study analyzes impacts of COVID-19 on French forestry sector, finds mixed results in supply chain.

problem Impact of COVID-19 on forestry sector supply chain and future opportunities.
method Integrated methodology combining Material Flow Analysis and Wood Product Model.
result Significant disruptions and shifts in wood production, highlighting resilience and vulnerabilities.

Framework generates realistic crop images for growth modeling.

problem Modeling crop growth over time with precision and detail.
method Two-stage framework: image prediction and growth estimation models.
result Framework accurately predicts crop images with varying conditions.

Polluting fine dusts in South Korea which are mainly consisted of biomass burning and fugitive dust blown from dust belt is significant problem these days. Predicting concentrations of fine dust particles in Seoul is challenging because they are product of complicate chemical reactions among gaseous pollutants and also…

2019-01-29abs ↗pdf ↗

Optimized DMD for fast atmospheric chemistry forecasting.

problem Forecasting global atmospheric chemistry dynamics efficiently.
method Optimized Dynamic Mode Decomposition (DMD) for reduced order modeling.
result Significant improvement in computational speed and interpretability.

Computer-assisted synthesis planning aims to help chemists find better reaction pathways faster. Finding viable and short pathways from sugar molecules to value-added chemicals can be modeled as a retrosynthesis planning problem with a catalyst allowed. This is a crucial step in efficient biomass conversion. The tradit…

2019-11-10abs ↗pdf ↗

Deep learning enhances smart fish farming through automated feature extraction.

problem Challenges in obtaining labeled data limit DL applications in aquaculture.
method Application of DL techniques in aquaculture, including live fish identification, species classification, and feeding decision-making.
result Deep learning's ability to automatically extract features is a significant contribution.