Abstract: This research aims to classify Diabetes Mellitus (DM) using the Random Forest (RF) model by exploring feature selection techniques and hyperparameter tuning. DM is a metabolic disorder in ...
As retired Forest Service leaders who had the privilege of managing millions of acres of national forests across the West, we understand the importance of stewarding these lands for the benefit of ...
The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...
This webinar will present a global synthesis on Payment for Ecosystem Services (PES) for forests, highlighting country experiences, good practices, and implementation challenges. It will provide ...
Despite the ‘whole of society’ engagement in the global climate Action Agenda since COP21, the world is still far off track to achieving the goals of the Paris Agreement. To course-correct, the world ...
A pioneering study reveals how archaeologists' satellite tools can be repurposed to tackle climate change. By using AI and satellite LiDAR imagery from NASA and ESA, researchers have found a faster, ...
ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...
The Oregon Department of Forestry (ODF) finalized its Implementation Plans that describe revisions for the Astoria, Forest Grove, Tillamook, North Cascade, West Oregon, and Western Lane (including the ...
The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
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