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This paper proposes a new method to classify architectural ceramic materials by using Genetic algorithm and Artificial Neural Network (ANN). And it addressed the training of a classifier for identification of architectural ceramic materials. By means of the global searching trait of genetic algorithm and the best searching trait of BP algorithm, the combination of them is the best way to optimize...
Bioinformatics analysis based on microarray technology is facing serious challenges, due to the extremely high dimensionality of the gene expression data comparing to the typical small number of available samples. Single artificial neural network was unstable and inaccurate for classification. In this paper we introduce classifying gene expression data using artificial neural network ensembles based...
Classification is an important problem in data mining. This paper focuses on a method of optimizing classifiers of neural network by Genetic Algorithm based on principle of gene reconfiguration, and implement classification by training the weight. The paper uses shift reverse logic crossover operation and the improved genetic algorithm The article using the typical method for optimizing BP neural...
Thalassemia is a genetic defect that is commonly found in many parts of the world. Number of humans that are suffering from this disease is determined by screening the heterozygous population. This article investigates the thalassemia screening problem using the unconstrained functional networks classifier. The learning algorithm for this new scheme is briefly illustrated. The new intelligent system...
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