Since the Neural Network (NN) with a Genetic Algorithm (GA) as a complement; are good optimization tools, we compare its performance with the Response Surface Methodology (RSM) that is generally used in the optimization of the process, in this case welding process. For the data used in the comparison, the results show that NN plus GA and RSM have a good results and very well performance, for identify the optimal set of parameters to obtain amaximum response of the process.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Optimization Welding Process Parameters through Response Surface, Neural Network and Genetic Algorithms


    Beteiligte:


    Erscheinungsdatum :

    01.09.2008


    Format / Umfang :

    280772 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    OPTIMIZATION OF ELECTRO-CHEMICAL MACHINING PROCESS PARAMETERS USING GENETIC ALGORITHMS

    Jain, N. K. / Jain, V. K. | British Library Online Contents | 2007


    Combining Multilayer Neural Network and Genetic Algorithms for Structural Optimization

    Furuya, H. / Lu, J. | British Library Conference Proceedings | 1999


    Composite Structural Optimization by Genetic Algorithm and Neural Network Response Surface Modeling

    Xu, Y.-m. / Li, S. / Rong, X.-m. | British Library Online Contents | 2005



    Genetic algorithms in bus network optimization

    Bielli, Maurizio | Online Contents | 2002