Analyzing Fe-Zn system using molecular dynamics, evolutionary neural nets and multi-objective genetic algorithms

Computational Materials Science

Volumn 46, Issue 4, 2009, Pages 821-827

  Bhattacharya, Baidurya ^a   Dinesh Kumar, G R ^a   Agarwal, Akash ^a   Erkoç, Şakir ^b   Singh, Arunima ^a   Chakraborti, Nirupam ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY   (India)

^b MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

Author keywords

Artificial neural networks; Fe Zn system; Genetic algorithms; Hot dip galvanizing; Molecular dynamics; Multi objective optimization

Indexed keywords

ARTIFICIAL NEURAL NETWORKS; DATA-DRIVEN MODEL; EVOLUTIONARY NEURAL NETWORK; FAILURE BEHAVIORS; FE-ZN SYSTEM; HOT-DIP GALVANIZING; MULTI-OBJECTIVE GENETIC ALGORITHM; NEURAL NET; PARETO FRONTIERS; SHEAR RATES;

BACKPROPAGATION; DYNAMICS; GALVANIZING; MOLECULAR DYNAMICS; MULTIOBJECTIVE OPTIMIZATION; NEURAL NETWORKS; SHEAR DEFORMATION; ZINC;

GENETIC ALGORITHMS;

EID: 70249094618     PISSN: 09270256     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.commatsci.2009.04.023     Document Type: Article

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