{"title":"基于人工神经网络的天体物理光谱聚类分析","authors":"P. Madhusudan, A. Amrutha, K. Venugopal","doi":"10.1109/ICCMC.2017.8282521","DOIUrl":null,"url":null,"abstract":"One of the largest sources of big data is data from space observatories which are spectral, optical and numerical in nature. The analysis of this data is often performed using conventional computing techniques utilising vast computational resources, typically supercomputers. Brute force algorithms often play a part in such computations. In this paper, a novel artificial neural network based clustering approach is proposed for spectral classification of stellar data.","PeriodicalId":163288,"journal":{"name":"2017 International Conference on Computing Methodologies and Communication (ICCMC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial neural network based clustering for analysis of astrophysical spectra\",\"authors\":\"P. Madhusudan, A. Amrutha, K. Venugopal\",\"doi\":\"10.1109/ICCMC.2017.8282521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the largest sources of big data is data from space observatories which are spectral, optical and numerical in nature. The analysis of this data is often performed using conventional computing techniques utilising vast computational resources, typically supercomputers. Brute force algorithms often play a part in such computations. In this paper, a novel artificial neural network based clustering approach is proposed for spectral classification of stellar data.\",\"PeriodicalId\":163288,\"journal\":{\"name\":\"2017 International Conference on Computing Methodologies and Communication (ICCMC)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Computing Methodologies and Communication (ICCMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCMC.2017.8282521\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computing Methodologies and Communication (ICCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMC.2017.8282521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial neural network based clustering for analysis of astrophysical spectra
One of the largest sources of big data is data from space observatories which are spectral, optical and numerical in nature. The analysis of this data is often performed using conventional computing techniques utilising vast computational resources, typically supercomputers. Brute force algorithms often play a part in such computations. In this paper, a novel artificial neural network based clustering approach is proposed for spectral classification of stellar data.