The paper describes a methodology for automatic hull form generation of ships with some desired performances using artificial intelligence techniques. The whole implementation process is divided into three main components. First of all the half-breadth weight matrices are generated that would provide population with pre-fitness by examining the relationship of the hull form with the principal dimensions of a number of existing vessels. Secondly, breadth and draft are adjusted using Neural Network Concepts. Breadth, draft, length, displacement and speed of the ship are very related terms and relations among them create some constraints. Neural Networks solve these constraints and adjust the parameters. Finally, Genetic Algorithm is used for searching the exact solution by examining several generations. For this, the algorithms need to measure fitness for every population in every generation. Unfortunately, GA doesn't guarantee fairness of the surface of the hull form, which can't be ignored. So, for every population especially for newborn population fairing techniques would be used. However, being complex geometric shape, hull form surface can't be faired using Ieast-square or other single equation fitting techniques. Fairness is done taking pair-wise points using B-spline functions (CAD 20(1988)).


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    Title :

    Application of artificial intelligence techniques in automatic hull form generation


    Additional title:

    Anwendung von Techniken der künstlichen Intelligenz zur automatischen Erzeugung von Schiffsrumpfformen


    Contributors:

    Published in:

    Ocean Engineering ; 28 , 12 ; 1531-1544


    Publication date :

    2001


    Size :

    14 Seiten, 4 Bilder, 3 Tabellen, 20 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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