{"title":"感知器、馈入和深度前馈人工神经网络在光谱数据上的应用:天体物理和聚变等离子体","authors":"N. Sakan, I. Traparić, V. Srećković, M. Ivković","doi":"10.31577/caosp.2022.52.3.97","DOIUrl":null,"url":null,"abstract":". Artificial neural networks are gaining a momentum for solving complex problems in all sorts of data analysis and classification matters. As such, idea of determining their usability on complex plasma came up. The choice for the input data for the analysis is a set of stellar spectral data. It consists of complex composition plasma under vast variety of conditions, dependent on type of star, measured with calibrated standardized procedures and equipment. The results of the analysis has shown that even a simple type of perceptron artificial neural network could lead to results of acceptable quality for the analysis of spectra of complex composition. The analyzed ANNs performed good on a limited data set. The results can be interpreted as a figure of merit for further development of complex neural networks in various applications e.g. in astrophysical and fusion plasmas.","PeriodicalId":50617,"journal":{"name":"Contributions of the Astronomical Observatory Skalnate Pleso","volume":" ","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The usage of perceptron, feed and deep feed forward artificial neural networks on the spectroscopy data: astrophysical & fusion plasmas\",\"authors\":\"N. Sakan, I. Traparić, V. Srećković, M. Ivković\",\"doi\":\"10.31577/caosp.2022.52.3.97\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". Artificial neural networks are gaining a momentum for solving complex problems in all sorts of data analysis and classification matters. As such, idea of determining their usability on complex plasma came up. The choice for the input data for the analysis is a set of stellar spectral data. It consists of complex composition plasma under vast variety of conditions, dependent on type of star, measured with calibrated standardized procedures and equipment. The results of the analysis has shown that even a simple type of perceptron artificial neural network could lead to results of acceptable quality for the analysis of spectra of complex composition. The analyzed ANNs performed good on a limited data set. The results can be interpreted as a figure of merit for further development of complex neural networks in various applications e.g. in astrophysical and fusion plasmas.\",\"PeriodicalId\":50617,\"journal\":{\"name\":\"Contributions of the Astronomical Observatory Skalnate Pleso\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Contributions of the Astronomical Observatory Skalnate Pleso\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.31577/caosp.2022.52.3.97\",\"RegionNum\":4,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ASTRONOMY & ASTROPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contributions of the Astronomical Observatory Skalnate Pleso","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.31577/caosp.2022.52.3.97","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
The usage of perceptron, feed and deep feed forward artificial neural networks on the spectroscopy data: astrophysical & fusion plasmas
. Artificial neural networks are gaining a momentum for solving complex problems in all sorts of data analysis and classification matters. As such, idea of determining their usability on complex plasma came up. The choice for the input data for the analysis is a set of stellar spectral data. It consists of complex composition plasma under vast variety of conditions, dependent on type of star, measured with calibrated standardized procedures and equipment. The results of the analysis has shown that even a simple type of perceptron artificial neural network could lead to results of acceptable quality for the analysis of spectra of complex composition. The analyzed ANNs performed good on a limited data set. The results can be interpreted as a figure of merit for further development of complex neural networks in various applications e.g. in astrophysical and fusion plasmas.
期刊介绍:
Contributions of the Astronomical Observatory Skalnate Pleso" (CAOSP) is published by the Astronomical Institute of the Slovak Academy of Sciences (SAS). The journal publishes new results of astronomical and astrophysical research, preferentially covering the fields of Interplanetary Matter, Stellar Astrophysics and Solar Physics. We publish regular papers, expert comments and review contributions.