1 - 3 of 3 articles
Machine learning techniques have to date not been widely used in population-environment research, but represent a promising tool for identifying relationships between environmental variables and population outcomes. They may be particularly useful for instances where the nature of the...
The Great Plains drought of 1931–1939 was a prolonged socio-ecological disaster with widespread impacts on society, economy, and health. While its immediate impacts are well documented, we know much less about the disaster’s effects on distal human outcomes. In particular, the event’s effects on...
Population densities provide valuable spatial information to identify populations at risk, quantify mobility, and improve our understanding of future urban settlements. Advancements in machine learning algorithms open up new horizons to face these challenges. This research proposes a supervised...
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Sign Up Log In
To subscribe to email alerts, please log in first, or sign up for a DeepDyve account if you don’t already have one.
To get new article updates from a journal on your personalized homepage, please log in first, or sign up for a DeepDyve account if you don’t already have one.