Disruption prediction and model analysis using LightGBM on J-TEXT and HL-2A
Sign Up to like & getrecommendations! Published in 2021 at "Plasma Physics and Controlled Fusion"
DOI: 10.1088/1361-6587/abfa74
Abstract: Using machine learning (ML) techniques to develop disruption predictors is an effective way to avoid or mitigate the disruption in a large-scale tokamak. The recent ML-based disruption predictors have made great progress regarding accuracy, but… read more here.
Keywords: disruption prediction; model; cross machine; disruption ... See more keywords
A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction
Sign Up to like & getrecommendations! Published in 2018 at "Indian Journal of Pharmacology"
DOI: 10.4103/ijp.ijp_304_17
Abstract: CONTEXT: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details create massive data… read more here.
Keywords: disruption prediction; big data; similarity; chemical ... See more keywords