Predictions of oil/chemical tanker main design parameters using computational intelligence techniques

Applied Soft Computing Journal

Volumn 11, Issue 2, 2011, Pages 2356-2366

  Ekinci, S ^a,b   Celebi, U B ^a,b   Bal, M ^a,b   Amasyali, M F ^a,b   Boyaci, U K ^a,b  

^a YILDIZ TECHNICAL UNIVERSITY   (Turkey)

^b SCIENTIFIC AND TECHNOLOGICAL RESEARCH COUNCIL OF TURKEY   (Turkey)

Author keywords

Computational intelligence; Machine learning; Naval engineering; Neural networks; Ship design main parameters

Indexed keywords

COMPUTATIONAL INTELLIGENCE; COMPUTATIONAL INTELLIGENCE METHODS; COMPUTATIONAL INTELLIGENCE TECHNIQUES; DESIGN PARAMETERS; DESIGN STAGE; MACHINE LEARNING; MAIN PARAMETERS; NAVAL ENGINEERING; SHIP DESIGN MAIN PARAMETERS; SHIP DESIGNS; SHIP MODELING; SPEED PARAMETERS;

ENGINEERING EDUCATION; EXPERIMENTS; LEARNING SYSTEMS; MACHINE DESIGN; MARINE ENGINEERING; NEURAL NETWORKS; PARAMETER ESTIMATION; SHIPBUILDING;

TANKERS (SHIPS);

EID: 78751609525     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2010.08.015     Document Type: Conference Paper

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