FP-STE: A Novel Node Failure Prediction Method Based on Spatio-Temporal Feature Extraction in Data Centers | Zendy

Yang Yang | Zendy; Jing Dong | Zendy; Chao Fang | Zendy; Ping Xie | Zendy; Na An | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

FP-STE: A Novel Node Failure Prediction Method Based on Spatio-Temporal Feature Extraction in Data Centers

Author(s) -

Yang Yang,

Jing Dong,

Chao Fang,

Ping Xie,

Na An

Publication year - 2020

Publication title -

computer modeling in engineering and sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.341

H-Index - 60

eISSN - 1526-1506

pISSN - 1526-1492

DOI - 10.32604/cmes.2020.09404

Subject(s) - computer science , oversampling , node (physics) , convolutional neural network , reliability (semiconductor) , cloud computing , data mining , feature extraction , artificial neural network , artificial intelligence , sample (material) , multivariate statistics , feature (linguistics) , machine learning , engineering , computer network , power (physics) , chemistry , physics , structural engineering , bandwidth (computing) , chromatography , quantum mechanics , operating system , linguistics , philosophy

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research