@article{scholars127,
         address = {Chengdu},
           title = {Meta-learning evolutionary artificial neural network for selecting flexible manufacturing systems},
             doi = {10.1007/11760191{$_1$}{$_3$}{$_0$}},
          volume = {3973 L},
            note = {cited By 4; Conference of 3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks ; Conference Date: 28 May 2006 Through 1 June 2006; Conference Code:67771},
           pages = {891--897},
       publisher = {Springer Verlag},
         journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
            year = {2006},
        abstract = {This paper proposes the application of Meta-Learning Evolutionary Artificial Neural Network (MLEANN) in selecting flexible manufacturing systems (FMS) from a group of candidate FMS's. First, multi-criteria decision-making (MCDM) methodology using an improved S-shaped membership function has been developed for finding out the 'best candidate FMS alternative' from a set of candidate-FMSs. The MCDM model trade-offs among various parameters, namely, design parameters, economic considerations, etc., affecting the FMS selection process in multi-criteria decision-making environment. Genetic algorithm is used to evolve the architecture and weights of the proposed neural network method. Further, a back-propagation (BP) algorithm is used as the local search algorithm. The selection of FMS is made according to the error output of the results found from the MCDM model. {\^A}{\copyright} Springer-Verlag Berlin Heidelberg 2006.},
        keywords = {Backpropagation; Decision making; Flexible manufacturing systems; Genetic algorithms; Learning systems; Membership functions; Parameter estimation, Back-propagation (BP) algorithm; Meta-Learning Evolutionary Artificial Neural Network (MLEANN); Multi-criteria decision-making; Search algorithm, Neural networks},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33745911288&doi=10.1007\%2f11760191\%5f130&partnerID=40&md5=54936ad14bb90f93b3ee8680f9a11d32},
            isbn = {3540344829; 9783540344827},
            issn = {03029743},
          author = {Bhattacharya, A. and Abraham, A. and Grosan, C. and Vasant, P. and Han, S.}
}