A hybrid ANN-BFOA approach for optimization of FDM process parameters

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6466 LNCS, Issue , 2010, Pages 396-403

  Sood, Anoop Kumar ^a   Ohdar, R K ^a   Mahapatra, S S ^b  

^a NATIONAL INSTITUTE OF FOUNDRY AND FORGE TECHNOLOGY   (India)

^b NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; BAYESIAN REGULARIZATION; EXPERIMENTAL DATA; FABRICATED PARTS; FUSED DEPOSITION MODELLING; GENERALIZATION CAPABILITY; HYBRID ANN; INTEGRATED APPROACH; LEVENBERG-MARQUARDT ALGORITHM; MECHANICAL STRENGTH; NETWORK PARAMETERS; NETWORK SIZE; OPTIMIZATION ALGORITHMS; OPTIMIZATION OF PROCESS PARAMETERS; OUTPUT RESPONSE; OVERFITTING; PARAMETER SETTING; PROCESS PARAMETERS; TRAINING AND TESTING; BACTERIAL FORAGING OPTIMIZATION ALGORITHM (BFOA);

EVOLUTIONARY ALGORITHMS; NETWORK ARCHITECTURE; OPTIMIZATION; NEURAL NETWORKS;

NEURAL NETWORKS; OPTIMIZATION;

EID: 78650888285     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-17563-3_48     Document Type: Conference Paper

References (6)

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