Predicting Protein Localization Sites in Escherichia Coli Bacteria

L. Parthiban
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Abstract

In this paper, three different neural network structure which are Self Organizing Map (SOM), Probablistic Neural Network (PNN) and Radial Basis Function (RBF) were applied to the Escherichia coli bacteria benchmark and their efficiency in classifying the dataset has been obtained Then the dataset is applied to the proposed coactive neuro-fuzzy inference system (CANFIS) model integrated with genetic algorithm and better classification with less MSE is obtained when tested using replicative testing.
预测大肠杆菌的蛋白定位位点
本文介绍了三种不同的神经网络结构,即自组织映射(SOM)、将概率神经网络(PNN)和径向基函数(RBF)应用于大肠杆菌基准,获得了对数据集的分类效率,然后将该数据集应用于结合遗传算法的协同神经模糊推理系统(CANFIS)模型,在重复测试中获得了较好的分类效果和较小的MSE。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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