{"title":"基于聚类算法的神经网络预处理新方法","authors":"Mariia Martynova, Ondrej Kaas","doi":"10.1109/SAMI.2019.8782767","DOIUrl":null,"url":null,"abstract":"This paper presents experiments in the preprocessing area for Radial Basic Function Neural Network (RBF NN). The main ideas of it are to find optimal pre-processing methods and algorithms, which can optimize input parameters and expedite the processing of neural network. The proposed methods are some novel experiments with flexible shape parameters and automated determination of the neural network initial parameters.","PeriodicalId":240256,"journal":{"name":"2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Methods Based on Clustering Algorithms as The Neural Network Preprocessing\",\"authors\":\"Mariia Martynova, Ondrej Kaas\",\"doi\":\"10.1109/SAMI.2019.8782767\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents experiments in the preprocessing area for Radial Basic Function Neural Network (RBF NN). The main ideas of it are to find optimal pre-processing methods and algorithms, which can optimize input parameters and expedite the processing of neural network. The proposed methods are some novel experiments with flexible shape parameters and automated determination of the neural network initial parameters.\",\"PeriodicalId\":240256,\"journal\":{\"name\":\"2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"47 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\":\"2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2019.8782767\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 17th World Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2019.8782767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Methods Based on Clustering Algorithms as The Neural Network Preprocessing
This paper presents experiments in the preprocessing area for Radial Basic Function Neural Network (RBF NN). The main ideas of it are to find optimal pre-processing methods and algorithms, which can optimize input parameters and expedite the processing of neural network. The proposed methods are some novel experiments with flexible shape parameters and automated determination of the neural network initial parameters.
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