{"title":"预测大肠杆菌的蛋白定位位点","authors":"L. Parthiban","doi":"10.18000/IJISAC.50128","DOIUrl":null,"url":null,"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.","PeriodicalId":216733,"journal":{"name":"Biometrics and Bioinformatics","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting Protein Localization Sites in Escherichia Coli Bacteria\",\"authors\":\"L. Parthiban\",\"doi\":\"10.18000/IJISAC.50128\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":216733,\"journal\":{\"name\":\"Biometrics and Bioinformatics\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biometrics and Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18000/IJISAC.50128\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biometrics and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18000/IJISAC.50128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting Protein Localization Sites in Escherichia Coli Bacteria
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.