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Modelling and Simulation in Materials Science and Engineering

Volumn 8, Issue 5, 2000, Pages 687-706

Accelerated learning using Gaussian process models to predict static recrystallization in an Al-Mg alloy

(3) Sabin, T J a,b Bailer Jones, C A L a,c Withers, P J a,d

a UNIVERSITY OF CAMBRIDGE (United Kingdom)

b TECHNICAL UNIVERSITY OF DENMARK (Denmark)

c MAX PLANCK INSTITUT FÜR ASTRONOMIE (Germany)

d UNIVERSITY OF MANCHESTER (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ANNEALING; COMPOSITE MICROMECHANICS; MATHEMATICAL MODELS; METALLOGRAPHIC MICROSTRUCTURE; PROBABILITY DISTRIBUTIONS; RECRYSTALLIZATION (METALLURGY); SPURIOUS SIGNAL NOISE;

ALUMINUM MAGNESIUM ALLOY; BAYESIAN FRAMEWORK; GAUSSIAN PROCESS;

ALUMINUM ALLOYS;

EID: 0034275003 PISSN: 09650393 EISSN: None Source Type: Journal
DOI: 10.1088/0965-0393/8/5/304 Document Type: Article

Times cited : (12)

References (19)

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