Digitale Bibliotheek
Sluiten Bladeren door artikelen uit een tijdschrift
 
   volgende >>
     Tijdschrift beschrijving
       Alle jaargangen van het bijbehorende tijdschrift
         Alle afleveringen van het bijbehorende jaargang
           Alle artikelen van de bijbehorende aflevering
                                       Details van artikel 1 van 6 gevonden artikelen
 
 
  A GENETIC NEURAL FUZZY SYSTEM AND ITS APPLICATION IN QUALITY PREDICTION IN THE INJECTION PROCESS
 
 
Titel: A GENETIC NEURAL FUZZY SYSTEM AND ITS APPLICATION IN QUALITY PREDICTION IN THE INJECTION PROCESS
Auteur: Li, Erguo
Jia, Li
Yu, Jinshou
Verschenen in: Chemical engineering communications
Paginering: Jaargang 191 (2004) nr. 3 pagina's 335-355
Jaar: 2004-03
Inhoud: A genetic neural fuzzy system (GNFS) is presented and introduced to quality prediction in the injection process. A hybrid-learning algorithm is proposed, which is divided into two stages to train GNFS. During the first learning stage, the genetic algorithm is used to optimize the structure of GNFS and the membership function of each fuzzy term because of its capability of parallel and global search. On the basis of the first optimized training stages, the back-propagation algorithm (BP algorithm) is adopted to update the parameters of the GNFS to improve its predicting precision and reduce the computation time. The process of constructing a quality prediction model for an injection process based on GNFS is described in detail. The predicted weight of the molded part from the model based on GNFS demonstrates that the proposed GNFS has superior performance and good generalization capability in quality prediction in the injection process.
Uitgever: Taylor & Francis
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details van artikel 1 van 6 gevonden artikelen
 
   volgende >>
 
 Koninklijke Bibliotheek - Nationale Bibliotheek van Nederland