@article{MAKHILLRJAS201510129698,
    title = {Application of Grammars of Kitano Graph Generation for Coding of Structure of Feedforward Artificial Neural Network},
    journal = {Research Journal of Applied Sciences},
    volume = {10},
    number = {12},
    pages = {815-818},
    year = {2015},
    issn = {1815-932x},
    doi = {rjasci.2015.815.818},
    url = {https://makhillpublications.co/view-article.php?issn=1815-932x&doi=rjasci.2015.815.818},
    author = {M.V.,N.V.,A.N.,A.V. and},
    keywords = {Artificial neural network,feedforward neural network,grammars of Kitano graph generation,Genetic algorithm,classification,tree-like classifier},
    abstract = {In this study, we have considered one of developments of grammars of Kitano graph generation theory as an approach to describing structure of feedforward Artificial Neural Network (ANN) within the context of application of Genetic algorithms for search of its optimal structure. We have described in details applied Genetic algorithm of search of optimal feedforward ANN structure. Results of the experiments have been provided within the framework of which solution for complex realization task was given, namely the task of dividing classes “Softwood forest” and “Mixed forest”.}
    }