Diagnosis of Fish Diseases Using Artificial Neural Networks
نویسندگان
چکیده
Artificial neural networks (ANNs) are computational intelligence techniques, which are used in many applications, such as disease diagnosis. The objective of this study was to evaluate two artificial neural networks created for the diagnosis of diseases in fish caused by protozoa and bacteria. As a classification system, ANNs are an important tool for decisionmaking in disease diagnosis. A back-propagation feed-forward was selected, with two layers, sigmoid and linear activation functions, and the Levenberg -Marquardat algorithm, for the training of the ANNs. The results of the application of these neural networks for the diagnosis of fish diseases based on test cases indicated a 97% success rate for the classification of both bacterial and protozoan diseases.
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