komimensah/Ecological-constraints-into-machine-learning-to-corrects-bias-and-improves-ecological-gradients-: Ecological constraints into machine learning

Domain:

agricultureenvironment and energy

Record type:

softwaredataset

Creator:

KOM

Publisher:

Host:

Here, we propose a hybrid approach that embeds a temperature-driven mechanistic suitability index into XGBoost through biologically informed sample weighting and apply it to desert locust (Schistocerca gregaria) occurrence in the Red Sea region of Sudan

Visit

doi.org

Licenses

info:eu-repo/semantics/openAccess MIT License https://opensource.org/licenses/MIT

Why Abundant Biomass Fails to Deliver: Machine Learning Insights into Biogas Production Constraints in Sub-Saharan Africa

Sub-Saharan Africa is rich in agricultural biomass, yet its biogas utilization is far below its pote

Robust ecological analysis of camera trap data labelled by a machine learning model

Ecological data are collected over vast geographic areas using digital sensors such as camera traps

From Climate Extremes to Risk: Quantifying Agro-Ecological Climate Vulnerability in Ghana Using Explainable Machine Learning

Climate extremes pose increasing risks to agro-ecological systems in sub-Saharan Africa, yet their d

Programming code for: Supporting ecological restoration: leveraging satellite data and machine learning to map invasive alien tree biomass

Programming code for: Supporting ecological restoration: leveraging

Learning about social-ecological trade-offs

International audience Trade-offs are manifestations of the complex dynamics in inter

Latent Ecological Sustainability Archetypes in Developing Countries: An Unsupervised Machine Learning Analysis of SDG Monitoring Data

Global sustainability monitoring relies on aggregated policy indicators that often obscure the nonli