Sign In

Communications of the ACM

ACM TechNews

Pattern Discovery Over Pattern Recognition: A New Way for Computers to See


The Community Climate System Model.

Researchers at the University of California, Davis are designing machine-learning systems to help supercomputers identify large-scale atmospheric structures, such as hurricanes and atmospheric rivers, in climate data.

Credit: PNNL

Researchers at the University of California, Davis are designing machine-learning systems to enable supercomputers to identify large-scale atmospheric structures, such as hurricanes and atmospheric rivers, in climate data.

The researchers conduct their experiments on the U.S. Department of Energy's National Energy Research Scientific Computing Center's CORI supercomputer.

Climate and weather systems change over time, so the researchers must find patterns not only in space but over time. They are developing algorithms that enable computers to identify structures in data without knowing what they are in advance.

A supercomputer can use pattern discovery to learn how to identify hurricanes or other features in climate and weather data, and it could be able to identify new kinds of structures that are too complex for humans to perceive.

From Egghead
View Full Article

 

Abstracts Copyright © 2017 Information Inc., Bethesda, Maryland, USA


 

No entries found

Read CACM in a free mobile app!
Access the latest issue, plus archived issues and more
ACM Logo
  • ACM CACM apps available for iPad, iPhone and iPod Touch, and Android platforms
  • ACM Digital Library apps available for iOS, Android, and Windows devices
  • Download an app and sign in to it with your ACM Web Account
Find the app for your mobile device
ACM DL Logo