Applications of Artificial Neutral Networks in Mushroom Edibility Classification

Applications of Artificial Neutral Networks in Mushroom Edibility Classification

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We report the accuracy of a two-layer, back-propagation artificial neural network in identifying edibility of a set of random mushrooms.Mushrooms edibility was synthesized using many different characteristics.Tests were run using texas bag ego different combinations of number of sapatilha infantil prata glitter hidden nodes, separation of training, validation, and test data and number of iterations.

Qualitative identification of an optimal combination of network parameters will provide a basis toward applications of artificial neural networks in future civil engineering endeavors.