Alia Karim Abdul Hassan; Sarah Sadoon Jasim
Abstract
In this work Aِِrtificial Neural Network (ANN) is used as a classifier capable ofrecognizing the most important features of the plant disease, with minimum errorvalue. Genetic algorithm ...
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In this work Aِِrtificial Neural Network (ANN) is used as a classifier capable ofrecognizing the most important features of the plant disease, with minimum errorvalue. Genetic algorithm has been used to minimize error values of the ANNclassifier. Error value of ANN classifier is defined as more than (%5). This ratiois a threshold (cut-of-value) to determine if GA is executed or not after the ANNclassifier execution. Genetic algorithm execution results in either optimal solution(%100) recognition or suggests a modified parameter to the ANN classifier(specifically learning rate and number of neurons).The result obtained fromintegrating neural network with genetic algorithm for classification plant diseasesindicates that the classifier recognizes most of input pattern with accuracy (96%).Integrating neural network with genetic algorithm for classification plant diseasesimplemented using Visual Basic version 6 programming
