We've updated our Privacy Policy to make it clearer how we use your personal data.

We use cookies to provide you with a better experience, read our Cookie Policy

Artificial Intelligence Helps Accelerate Fusion Reaction Efficiency

News   Dec 15, 2017 | Original story from Princeton Plasma Physics Laboratory (PPPL)

 
Artificial Intelligence Helps Accelerate Fusion Reaction Efficiency

Image of plasma disruption in experiment on JET, left, and disruption-free experiment on JET, right. Training the FRNN neural network to predict disruptions calls for assigning weights to the data flow along the connections between nodes. Data from new experiments is then put through the network, which predicts "disruption" or "non-disruption." The ultimate goal is at least 95 percent correct predictions of disruption events. Image and explanation courtesy of Eliot Feibush.

 
 
 

RELATED ARTICLES

Unprecedented View of Gene Therapy Virus

News

Using cryo-electron microscopy, scientists have obtained an unprecedented view of a gene-delivery virus, paving the way for further development of improved gene therapies.

READ MORE

Computational Models of the Human Lung: Potential for Personalized Medicine & Inhalation Toxicology

News

Combining high-performance computing, high-fidelity modeling, and high-resolution medical imaging, produces simulations that have the potential to contribute to new diagnostic tools and treatment options for respiratory disease.

READ MORE

Neural Network Scrapes Social Media to Diagnose Disease

News

“Cannot get asleep all night”, “a little giddy” and other complaints in social networks can now be translated into formal medical terms, such as insomnia or vertigo, after a Russian-led study involving neural networks.

READ MORE

 

To personalize the content you see on Technology Networks homepage, Log In or Subscribe for Free

LOGIN SUBSCRIBE FOR FREE