Artificial neural networks generation using grammatical evolution

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@InProceedings{Soltanian:2013:ICEE,

• author = "Khabat Soltanian and Fardin Akhlaghian Tab and Fardin Ahmadi Zar and Ioannis Tsoulos",
• title = "Artificial neural networks generation using grammatical evolution",
• booktitle = "21st Iranian Conference on Electrical Engineering (ICEE 2013)",
• year = "2013",
• address = "Mashhad, Iran",
• month = "14-16 " # may,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, grammatical evolution, artificial neural networks, evolutionary computing, classification problems",
• ISSN = "2164-7054",
• DOI = "doi:10.1109/IranianCEE.2013.6599788",
• size = "5 pages",
• abstract = "in this paper an automatic artificial neural network generation method is described and evaluated. The proposed method generates the architecture of the network by means of grammatical evolution and uses back propagation algorithm for training it. In order to evaluate the performance of the method, a comparison is made against five other methods using a series of classification benchmarks. In the most cases it shows the superiority to the compared methods. In addition to the good experimental results, the ease of use is another advantage of the method since it works with no need of experts.",
• notes = "Also known as \cite{6599788}",

}

Genetic Programming entries for Khabat Soltanian Fardin Akhlaghian Tab Fardin Ahmadizar Ioannis G Tsoulos

Citations